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Vladik Kreinovich
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- affiliation: University of Texas at El Paso, Department of Computer Science, TX, USA
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2020 – today
- 2025
- [j444]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 33(1): 141-142 (2025) - [c314]Niklas R. Winnewisser, Michael Beer
, Olga Kosheleva
, Vladik Kreinovich
:
What Is Optimal Granularity When Estimating Reliability of a Complex Engineering Systems. IUKM (2) 2025: 76-84 - [c313]Niklas R. Winnewisser, Michael Beer
, Olga Kosheleva
, Vladik Kreinovich
:
How Shapley Value and Its Generalizations Can Help in the Analysis of Complex Engineering Systems and What Next. IUKM (2) 2025: 85-97 - [i7]Verya Monjezi, Ashutosh Trivedi, Vladik Kreinovich, Saeid Tizpaz-Niari:
Fairness Testing through Extreme Value Theory. CoRR abs/2501.11597 (2025) - 2024
- [j443]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 32(1): 131-132 (2024) - [j442]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 32(2): 271-272 (2024) - [j441]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 32(5): 831-832 (2024) - [j440]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 32(6): 1013-1014 (2024) - [j439]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 32(8): 1245-1246 (2024) - [j438]Olga Kosheleva, Vladik Kreinovich, Victor L. Timchenko
, Yuriy P. Kondratenko:
From Fuzzy to Mobile Fuzzy. J. Mobile Multimedia 20(3): 651-664 (2024) - [j437]Martine Ceberio, Christoph Quirin Lauter, Vladik Kreinovich:
Just-in-Accuracy: Mobile Approach to Uncertainty. J. Mobile Multimedia 20(3): 665-678 (2024) - [j436]Victor L. Timchenko
, Yuriy P. Kondratenko, Vladik Kreinovich:
Logical Platforms for Mobile Application in Decision Support Systems Based on Color Information Processing. J. Mobile Multimedia 20(3): 679-698 (2024) - [c312]María L. Reyna Cruz
, Ricardo Tabares
, Martine Ceberio
, Vladik Kreinovich
, Christoph Quirin Lauter
, Cecilia A. Márquez Barraza:
Machine Learning-Based Screening for Pediatric Hip Dysplasia: Towards a Validated Approach. IEEECONF 2024: 1891-1894 - [c311]Victor L. Timchenko, Vladik Kreinovich, Yuriy P. Kondratenko:
Color optical computing: visualization, numbers, alphabet. ICST 2024: 123-132 - [c310]Niklas R. Winnewisser
, Michael Beer
, Vladik Kreinovich
, Olga Kosheleva
:
From Quantifying and Propagating Uncertainty to Quantifying and Propagating Both Uncertainty and Reliability: Practice-Motivated Approach to Measurement Planning and Data Processing. IPMU (1) 2024: 389-402 - [c309]Salvador Robles Herrera
, Verya Monjezi
, Vladik Kreinovich
, Ashutosh Trivedi
, Saeid Tizpaz-Niari
:
Predicting Fairness of ML Software Configurations. PROMISE 2024: 56-65 - [c308]Olga Kosheleva, Vladik Kreinovich, Ahnaf Farhan:
Fuzzy Ideas Explain Fechner Law and Help Detect Relation Between Objects in Video. SACI 2024: 127-132 - [c307]Olga Kosheleva
, Vladik Kreinovich
:
Gifted and Talented: With Others? Separately? Mathematical Analysis of the Problem. SIGITE 2024: 138-141 - [c306]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Hung T. Nguyen:
Towards an Optimal Design: What Can We Recommend to Elon Musk? SMC 2024: 1189-1190 - [c305]Mirtill-Boglárka Naghi, Vladik Kreinovich, Levente Kovács, László Szilágyi:
A Self-Tuning Version for the Fuzzy-Possibilistic Product Partition c-Means Algorithm. SMC 2024: 4861-4867 - [p169]Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich:
Fuzzy Techniques Explain the Effectiveness of ReLU Activation Function in Deep Learning. New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics 2024: 425-430 - [p168]Aaron Velasco, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich:
Why 6-Labels Uncertainty Scale in Geosciences: Probability-Based Explanation. New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics 2024: 431-434 - [i6]Salvador Robles Herrera, Verya Monjezi, Vladik Kreinovich, Ashutosh Trivedi, Saeid Tizpaz-Niari:
Predicting Fairness of ML Software Configuration. CoRR abs/2404.19100 (2024) - 2023
- [b6]Vladik Kreinovich, Graçaliz Pereira Dimuro
, Antônio Carlos da Rocha Costa
:
From Intervals to -? - Towards a General Description of Validated Uncertainty. Studies in Computational Intelligence 1041, Springer 2023, ISBN 978-3-031-20568-2, pp. 1-116 - [j435]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(2): 351-352 (2023) - [j434]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(4): 711-712 (2023) - [j433]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(5): 889-890 (2023) - [j432]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(6): 1061-1062 (2023) - [j431]Hung T. Nguyen, Vladik Kreinovich:
Guest Editorial: Uncertainty in Economics and Finance. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(Supplement-2) (2023) - [j430]Orsolya Csiszár
, Luca Sára Pusztaházi
, Lehel Dénes-Fazakas
, Michael S. Gashler
, Vladik Kreinovich, Gábor Csiszár
:
Uninorm-like parametric activation functions for human-understandable neural models. Knowl. Based Syst. 260: 110095 (2023) - [j429]Hung T. Nguyen, Vladik Kreinovich:
Why Linear (and Piecewise Linear) Models Often Successfully Describe Complex Non-Linear Economic and Financial Phenomena: A~Fuzzy-Based Explanation. TFSS 2(1): 147-157 (2023) - [c304]Mehran Mazandarani
, Olga Kosheleva
, Vladik Kreinovich
:
Why Fractional Fuzzy. EUSFLAT/AGOP 2023: 285-296 - [c303]Victor L. Timchenko
, Yury P. Kondratenko, Vladik Kreinovich
:
Interval-Valued and Set-Valued Extensions of Discrete Fuzzy Logics, Belnap Logic, and Color Optical Computing. EUSFLAT/AGOP 2023: 297-303 - [c302]Victor L. Timchenko
, Yuriy P. Kondratenko, Vladik Kreinovich:
Logical Decision Networks Based on the Optical Coloroids. IDAACS 2023: 1194-1199 - [c301]Victor L. Timchenko, Yury P. Kondratenko, Vladik Kreinovich:
The Architecture of Optical Logical Coloroid with Fuzzy Computing. IntelITSIS 2023: 638-648 - [c300]Saeid Tizpaz-Niari, Luc Longpré, Olga Kosheleva
, Vladik Kreinovich
:
Fast - Asymptotically Optimal - Methods for Determining the Optimal Number of Features. IUKM (1) 2023: 123-128 - [c299]Edgar Daniel Rodriguez Velasquez, Aaron Velasco
, Olga Kosheleva
, Vladik Kreinovich
:
Why Inverse Layers in Pavement? Why Zipper Fracking? Why Interleaving in Education? a General Explanation. IUKM (1) 2023: 129-138 - [c298]Barnabás Bede, Vladik Kreinovich, Peter Toth:
Equivalence Between 1-D Takagi-Sugeno Fuzzy Systems with Triangular Membership Functions and Neural Networks with ReLU Activation. NAFIPS 2023: 44-56 - [c297]Vladik Kreinovich:
Theoretical Explanation of Bernstein Polynomials' Efficiency. NAFIPS 2023: 115-126 - [c296]Christian Servin, Aaron Velasco
, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich:
Everything is a Matter of Degree: The Main Idea Behind Fuzzy Logic is Useful in Geosciences and in Authorship. NAFIPS 2023: 219-227 - [c295]Martine Ceberio, Vladik Kreinovich, Olga Kosheleva, Günter Mayer:
Complex-Valued Interval Computations are NP-Hard Even for Single Use Expressions. NAFIPS 2023: 246-257 - [c294]Cliff A. Joslyn, Andrés Ortiz-Muñoz, Edgar Daniel Rodriguez Velasquez, Olga Kosheleva, Vladik Kreinovich:
Causality: Hypergraphs, Matter of Degree, Foundations of Cosmology. NAFIPS 2023: 279-289 - [c293]Martine Ceberio, Vladik Kreinovich, Olga Kosheleva, Lev Ginzburg:
Faster Algorithms for Estimating the Mean of a Quadratic Expression Under Uncertainty. NAFIPS 2023: 290-300 - [c292]Palvi Aggarwal, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
How People Make Decisions Based on Prior Experience: Formulas of Instance-Based Learning Theory (IBLT) Follow from Scale Invariance. NAFIPS 2023: 312-319 - [c291]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Integrity First, Service Before Self, and Excellence: Core Values of US Air Force Naturally Follow from Decision Theory. NAFIPS 2023: 320-324 - [c290]Sofia Holguin, Vladik Kreinovich:
Conflict Situations are Inevitable When There are Many Participants: A Proof Based on the Analysis of Aumann-Shapley Value. NAFIPS 2023: 325-330 - [c289]Vladik Kreinovich:
Computing at Least One of Two Roots of a Polynomial is, in General, Not Algorithmic. NAFIPS 2023: 331-334 - [c288]Juan A. Lopez, Vladik Kreinovich:
Towards Decision Making Under Interval Uncertainty. NAFIPS 2023: 335-337 - [c287]Miroslav Svítek, Olga Kosheleva, Vladik Kreinovich:
What Do Goedel's Theorem and Arrow's Theorem have in Common: A Possible Answer to Arrow's Question. NAFIPS 2023: 338-343 - [c286]Aaron Velasco, Olga Kosheleva, Vladik Kreinovich:
High-Impact Low-Probability Events are Even More Important Than it is Usually Assumed. NAFIPS 2023: 344-349 - [c285]Jieqiong Zhao, Olga Kosheleva, Vladik Kreinovich:
People Prefer More Information About Uncertainty, but Perform Worse When Given This Information: An Explanation of the Paradoxical Phenomenon. NAFIPS 2023: 350-356 - [c284]Lehel Dénes-Fazakas
, László Szilágyi, György Eigner, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Which Activation Function Works Best for Training Artificial Pancreas: Empirical Fact and Its Theoretical Explanation. SSCI 2023: 496-500 - [c283]Orsolya Csiszár, Gábor Csiszár, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Why Fuzzy Control Is Often More Robust (and Smoother): A Theoretical Explanation. SSCI 2023: 501-505 - [p167]Adilene Alaniz, Jiovani Hernandez, Andres D. Muñoz, Vladik Kreinovich:
Hunting Habits of Predatory Birds: Theoretical Explanation of an Empirical Formula. Uncertainty, Constraints, and Decision Making 2023: 3-6 - [p166]Luc Longpré, Olga Kosheleva, Vladik Kreinovich:
Baudelaire's Ideas of Vagueness and Uniqueness in Art: Algorithm-Based Explanations. Decision Making Under Uncertainty and Constraints 2023: 3-9 - [p165]Laxman Bokati
, Vladik Kreinovich, Joseph Baca, Natasha Rovelli:
Why Rectified Power (RePU) Activation Functions are Efficient in Deep Learning: A Theoretical Explanation. Uncertainty, Constraints, and Decision Making 2023: 7-13 - [p164]Olga Kosheleva, Vladik Kreinovich:
Selfish Gene Theory Explains Oedipus Complex. Decision Making Under Uncertainty and Constraints 2023: 13-16 - [p163]Demetrius R. Hernandez, George M. Molina Holguin, Francisco Parra, Vivian Sanchez, Vladik Kreinovich:
Aquatic Ecotoxicology: Theoretical Explanation of Empirical Formulas. Uncertainty, Constraints, and Decision Making 2023: 15-20 - [p162]Olga Kosheleva, Vladik Kreinovich:
How to Teach Advanced Highly Motivated Students: Teaching Strategy of Iosif Yakovlevich Verebeichik. Decision Making Under Uncertainty and Constraints 2023: 19-24 - [p161]Sofia Holguin, Vladik Kreinovich:
How Hot is Too Hot. Uncertainty, Constraints, and Decision Making 2023: 21-27 - [p160]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Why 70/100 Is Satisfactory? Why Five Letter Grades? Why Other Academic Conventions? Decision Making Under Uncertainty and Constraints 2023: 25-32 - [p159]Sofia Holguin, Vladik Kreinovich:
How Order and Disorder Affect People's Behavior: An Explanation. Uncertainty, Constraints, and Decision Making 2023: 29-32 - [p158]Sofia Holguin, Vladik Kreinovich:
Shape of an Egg: Towards a Natural Simple Universal Formula. Uncertainty, Constraints, and Decision Making 2023: 33-38 - [p157]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Shall We Ignore All Intermediate Grades? Decision Making Under Uncertainty and Constraints 2023: 33-38 - [p156]Olga Kosheleva, Vladik Kreinovich:
Why ∞ is a Reasonable Symbol for Infinity. Decision Making Under Uncertainty and Constraints 2023: 39-41 - [p155]Olga Kosheleva, Vladik Kreinovich:
A General Commonsense Explanation of Several Medical Results. Uncertainty, Constraints, and Decision Making 2023: 39-43 - [p154]Olga Kosheleva, Vladik Kreinovich:
What Is 1/0 from the Practical Viewpoint: A Pedagogical Note. Decision Making Under Uncertainty and Constraints 2023: 43-47 - [p153]Joshua Ramos, Ruth Trejo, Dario Vazquez, Vladik Kreinovich:
Why Immunodepressive Drugs Often Make People Happier. Uncertainty, Constraints, and Decision Making 2023: 45-48 - [p152]Francisco Zapata, Eric Smith, Vladik Kreinovich:
Systems Approach Explains Why Low Heart Rate Variability is Correlated with Depression (and Suicidal Thoughts). Uncertainty, Constraints, and Decision Making 2023: 49-53 - [p151]Sean R. Aguilar, Vladik Kreinovich:
How to Make Inflation Optimal and Fair. Uncertainty, Constraints, and Decision Making 2023: 57-61 - [p150]Sean R. Aguilar, Vladik Kreinovich:
Why Seneca Effect? Uncertainty, Constraints, and Decision Making 2023: 63-67 - [p149]Sean R. Aguilar, Olga Kosheleva, Vladik Kreinovich:
Why Base-20, Base-40, and Base-60 Number Systems? Decision Making Under Uncertainty and Constraints 2023: 63-67 - [p148]Laxman Bokati
, Olga Kosheleva, Vladik Kreinovich:
Why Rarity Score Is a Good Evaluation of a Non-Fungible Token. Uncertainty, Constraints, and Decision Making 2023: 69-74 - [p147]Olga Kosheleva, Vladik Kreinovich:
Why Chomsky Normal Form: A Pedagogical Note. Decision Making Under Uncertainty and Constraints 2023: 69-73 - [p146]Martine Ceberio, Christian Servin, Olga Kosheleva, Vladik Kreinovich:
How to Best Write Research Papers: Basic English? Sophisticated English? Decision Making Under Uncertainty and Constraints 2023: 75-80 - [p145]Alan Gamez, Antonio Aguirre, Christian Cordova, Alberto Miranda, Vladik Kreinovich:
Resource Allocation for Multi-tasking Optimization: Explanation of an Empirical Formula. Uncertainty, Constraints, and Decision Making 2023: 75-78 - [p144]Olga Kosheleva, Vladik Kreinovich:
Everyone is Above Average: Is It Possible? Is It Good? Uncertainty, Constraints, and Decision Making 2023: 79-83 - [p143]Mariana Benítez, Jeffrey Weidner, Vladik Kreinovich:
How to Select Typical Objects. Decision Making Under Uncertainty and Constraints 2023: 83-87 - [p142]Olga Kosheleva, Vladik Kreinovich:
How Probable is a Revolution? A Natural ReLU-Like Formula That Fits the Historical Data. Uncertainty, Constraints, and Decision Making 2023: 85-90 - [p141]Julio C. Urenda, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why Homogeneous Membranes Lead to Optimal Water Desalination: A Possible Explanation. Decision Making Under Uncertainty and Constraints 2023: 89-92 - [p140]Olga Kosheleva, Vladik Kreinovich:
Why Should Exactly 1/4 Be Returned to the Original Owner: An Economic Explanation of an Ancient Recommendation. Uncertainty, Constraints, and Decision Making 2023: 91-94 - [p139]Hector A. Reyes, Dillon Trinh, Vladik Kreinovich:
Fault Detection in a Smart Electric Grid: Geometric Analysis. Decision Making Under Uncertainty and Constraints 2023: 93-99 - [p138]Olga Kosheleva, Vladik Kreinovich:
Why Would Anyone Invest in a High-Risk Low-Profit Enterprise? Uncertainty, Constraints, and Decision Making 2023: 95-98 - [p137]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Vladik Kreinovich:
Which Interval-Valued Alternatives Are Possibly Optimal if We Use Hurwicz Criterion. Uncertainty, Constraints, and Decision Making 2023: 99-104 - [p136]Daniela Flores, Olga Kosheleva, Vladik Kreinovich:
Why Geological Regions? Decision Making Under Uncertainty and Constraints 2023: 103-108 - [p135]Christopher Reyes, Vladik Kreinovich:
How to Solve the Apportionment Paradox. Uncertainty, Constraints, and Decision Making 2023: 105-108 - [p134]Miroslav Svítek, Olga Kosheleva, Vladik Kreinovich:
In the Absence of Information, the only Reasonable Negotiation Scheme Is Offering a Certain Percentage of the Original Request: A Proof. Uncertainty, Constraints, and Decision Making 2023: 109-113 - [p133]Daniel Cruz, Ricardo V. Godoy, Vladik Kreinovich:
Why, in Deep Learning, Non-smooth Activation Function Works Better Than Smooth Ones. Decision Making Under Uncertainty and Constraints 2023: 111-115 - [p132]Sofia Holguin, Vladik Kreinovich:
Why Residual Neural Networks. Decision Making Under Uncertainty and Constraints 2023: 117-120 - [p131]Olga Kosheleva, Vladik Kreinovich:
How to Make Quantum Ideas Less Counter-Intuitive: A Simple Analysis of Measurement Uncertainty Can Help. Uncertainty, Constraints, and Decision Making 2023: 117-122 - [p130]Olga Kosheleva, Vladik Kreinovich:
Why Semi-supervised Learning Makes Sense: A Pedagogical Note. Decision Making Under Uncertainty and Constraints 2023: 121-124 - [p129]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Physical Meaning Often Leads to Natural Derivations in Elementary Mathematics: On the Examples of Solving Quadratic and Cubic Equations. Uncertainty, Constraints, and Decision Making 2023: 123-126 - [p128]Ricardo Mendez, Osagumwenro Osaretin, Vladik Kreinovich:
How to Gauge the Quality of a Multi-class Classification When Ground Truth Is Known with Uncertainty. Decision Making Under Uncertainty and Constraints 2023: 125-128 - [p127]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Towards Better Ways to Compute the Overall Grade for a Class. Uncertainty, Constraints, and Decision Making 2023: 127-133 - [p126]Evgeny Dantsin, Vladik Kreinovich, Alexander Wolpert:
An AlphaZero-Inspired Approach to Solving Search Problems. Decision Making Under Uncertainty and Constraints 2023: 129-138 - [p125]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Why Some Theoretically Possible Representations of Natural Numbers Were Historically Used and Some Were Not: An Algorithm-Based Explanation. Uncertainty, Constraints, and Decision Making 2023: 135-139 - [p124]Julio C. Urenda, Sean R. Aguilar, Olga Kosheleva, Vladik Kreinovich:
Fuzzy Techniques, Laplace Indeterminacy Principle, and Maximum Entropy Approach Explain Lindy Effect and Help Avoid Meaningless Infinities in Physics. Decision Making Under Uncertainty and Constraints 2023: 141-152 - [p123]Alexis Lupo, Vladik Kreinovich:
Dielectric Barrier Discharge (DBD) Thrusters-Aerospace Engines of the Future: Invariance-Based Analysis. Uncertainty, Constraints, and Decision Making 2023: 143-148 - [p122]Hector A. Reyes, Aaron D. Brown, Jeffrey Escamilla, Ethan D. Kish, Vladik Kreinovich:
Need for Optimal Distributed Measurement of Cumulative Quantities Explains the Ubiquity of Absolute and Relative Error Components. Uncertainty, Constraints, and Decision Making 2023: 149-155 - [p121]Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich:
Dimension Compactification Naturally Follows from First Principles. Decision Making Under Uncertainty and Constraints 2023: 153-157 - [p120]Hector A. Reyes, Saeid Tizpaz-Niari, Vladik Kreinovich:
Over-Measurement Paradox: Suspension of Thermonuclear Research Center and Need to Update Standards. Uncertainty, Constraints, and Decision Making 2023: 157-164 - [p119]Lidice Castro, Vladik Kreinovich:
Is Our World Becoming Less Quantum? Decision Making Under Uncertainty and Constraints 2023: 159-163 - [p118]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
How to Get the Most Accurate Measurement-Based Estimates. Uncertainty, Constraints, and Decision Making 2023: 165-175 - [p117]Miroslav Svítek, Olga Kosheleva, Vladik Kreinovich:
As Complexity Rises, Meaningful Statements Lose Precision - But Why? Decision Making Under Uncertainty and Constraints 2023: 167-171 - [p116]David Amparan, Vladik Kreinovich:
Why People Overestimate Small Probabilities? Decision Making Under Uncertainty and Constraints 2023: 173-176 - [p115]Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich:
How to Estimate the Present Serviceability Rating of a Road Segment: Explanation of an Empirical Formula. Uncertainty, Constraints, and Decision Making 2023: 177-180 - [p114]Joshua Zamora, Vladik Kreinovich:
Why Ovals in Eliciting Intervals? Decision Making Under Uncertainty and Constraints 2023: 177-179 - [p113]R. Noah Padilla, Vladik Kreinovich:
Why Moments (and Generalized Moments) Are Used in Statistics and Why Expected Utility Is Used in Decision Making: A Possible Explanation. Decision Making Under Uncertainty and Constraints 2023: 181-187 - [p112]Leonel Escapita, Diana Licon, Madison Anderson, Diego Pedraza, Vladik Kreinovich:
Word Representation: Theoretical Explanation of an Empirical Fact. Uncertainty, Constraints, and Decision Making 2023: 183-187 - [p111]Toshiki Kamio, Gavin Baechle, Vladik Kreinovich:
Decision Making Under Uncertainty: Cases When We Only Know an Upper Bound or a Lower Bound. Decision Making Under Uncertainty and Constraints 2023: 189-192 - [p110]Julio C. Urenda, Vladik Kreinovich:
Why Menzerath's Law? Uncertainty, Constraints, and Decision Making 2023: 189-192 - [p109]Christopher Reyes, Vladik Kreinovich:
Why Do People Become Addicted: Towards a Theoretical Explanation for Eyal's Experiment-Based Hook Model. Decision Making Under Uncertainty and Constraints 2023: 193-199 - [p108]Jonatan M. Contreras, Martine Ceberio, Vladik Kreinovich:
One More Physics-Based Explanation for Rectified Linear Neurons. Uncertainty, Constraints, and Decision Making 2023: 195-198 - [p107]Ricardo Lozano, Ivan Montoya Sanchez, Vladik Kreinovich:
Why Deep Neural Networks: Yet Another Explanation. Uncertainty, Constraints, and Decision Making 2023: 199-202 - [p106]Leonardo Orea Amador, Vladik Kreinovich:
Why Decimal System? Why Communities with More Than 150 Folks Tend to Split? New Consequences of the Seven Plus Minus Two Law. Decision Making Under Uncertainty and Constraints 2023: 201-205 - [p105]Olga Kosheleva, Vladik Kreinovich:
Really Good Theorems Are Those That End Their Life as Definitions: Why. Uncertainty, Constraints, and Decision Making 2023: 205-208 - [p104]Olga Kosheleva, Vladik Kreinovich:
Lev Landau's Marital Advice Explained. Decision Making Under Uncertainty and Constraints 2023: 207-210 - [p103]Ricardo Alvarez, Yamel Hernandez, Vladik Kreinovich:
Why Too Much Interaction Between Different Parts of the Brain Leads To Unhappiness. Decision Making Under Uncertainty and Constraints 2023: 211-214 - [p102]Luc Longpré, Vladik Kreinovich:
How to Describe Hypothetic Truly Rare Events (With Probability 0). Uncertainty, Constraints, and Decision Making 2023: 211-215 - [p101]Olga Kosheleva, Vladik Kreinovich:
Gödel's Proof of Existence of God Revisited. Decision Making Under Uncertainty and Constraints 2023: 217-221 - [p100]Juan L. Puebla, Vladik Kreinovich:
Spiral Arms Around a Star: Geometric Explanation. Uncertainty, Constraints, and Decision Making 2023: 217-221 - [p99]Olga Kosheleva, Vladik Kreinovich:
Blessings, God, Sacrifices: Possible Rational Explanations of Biblical Ideas. Decision Making Under Uncertainty and Constraints 2023: 223-229 - [p98]Edgar Daniel Rodriguez Velasquez, Olga Kosheleva, Vladik Kreinovich:
Why Physical Power Laws Usually Have Rational Exponents. Uncertainty, Constraints, and Decision Making 2023: 223-226 - [p97]Miroslav Svítek, Olga Kosheleva, Vladik Kreinovich:
Freedom of Will, Non-uniqueness of Cauchy Problem, Fractal Processes, Renormalization, Phase Transitions, and Stealth Aircraft. Uncertainty, Constraints, and Decision Making 2023: 227-231 - [p96]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
Why Model Order Reduction. Decision Making Under Uncertainty and Constraints 2023: 233-237 - [p95]Miroslav Svítek, Vladik Kreinovich:
How Can the Opposite to a True Theory Be Also True? A Similar Talmudic Discussion Helps Make This Famous Bohr's Statement Logically Consistent. Uncertainty, Constraints, and Decision Making 2023: 233-236 - [p94]Saeid Tizpaz-Niari, Olga Kosheleva, Vladik Kreinovich:
How to Detect (and Analyze) Independent Subsystems of a Black-Box (or Grey-Box) System. Uncertainty, Constraints, and Decision Making 2023: 237-249 - [p93]Oscar Galindo, Christopher Ibarra, Vladik Kreinovich, Michael Beer
:
Fourier Transform and Other Quadratic Problems Under Interval Uncertainty. Decision Making Under Uncertainty and Constraints 2023: 251-256 - [p92]Sean R. Aguilar, Vladik Kreinovich:
Why Decision Paralysis. Uncertainty, Constraints, and Decision Making 2023: 253-255 - [p91]Laxman Bokati
, Vladik Kreinovich:
Why Time Seems to Pass Slowly for Unpleasant Experiences and Quickly for Pleasant Experiences: An Explanation Based on Decision Theory. Uncertainty, Constraints, and Decision Making 2023: 257-261 - [p90]Olga Kosheleva, Vladik Kreinovich:
How to Deal with Conflict of Interest Situations When Selecting the Best Submission. Uncertainty, Constraints, and Decision Making 2023: 263-267 - [p89]Olga Kosheleva, Vladik Kreinovich:
Why Aspirational Goals: Geometric Explanation. Uncertainty, Constraints, and Decision Making 2023: 269-273 - [p88]Olga Kosheleva, Vladik Kreinovich:
Why Hate: Analysis Based on Decision Theory. Uncertainty, Constraints, and Decision Making 2023: 275-279 - [p87]Oscar Ortiz, Henry Salgado, Olga Kosheleva, Vladik Kreinovich:
Why Self-Esteem Helps to Solve Problems: An Algorithmic Explanation. Uncertainty, Constraints, and Decision Making 2023: 281-286 - [p86]Javier Tellez, Wenbo Xie, Vladik Kreinovich:
Commonsense "And"-Operations. Decision Making Under Uncertainty and Constraints 2023: 285-288 - [p85]Miroslav Svítek, Olga Kosheleva, Vladik Kreinovich:
Why Five Stages of Solar Activity, Why Five Stages of Grief, Why Seven Plus Minus Two: A General Geometric Explanation. Uncertainty, Constraints, and Decision Making 2023: 287-292 - [p84]Javier Viaña
, Stephan Ralescu, Kelly Cohen
, Anca L. Ralescu, Vladik Kreinovich:
Extension to Multidimensional Problems of a Fuzzy-Based Explainable and Noise-Resilient Algorithm. Decision Making Under Uncertainty and Constraints 2023: 289-296 - [p83]Alejandra De La Peña, Damian L. Gallegos Espinoza, Vladik Kreinovich:
Anomaly Detection in Crowdsourcing: Why Midpoints in Interval-Valued Approach. Uncertainty, Constraints, and Decision Making 2023: 295-299 - [p82]Luc Longpré, Olga Kosheleva, Vladik Kreinovich:
Additional Spatial Dimensions Can Help Speed Up Computations. Decision Making Under Uncertainty and Constraints 2023: 297-304 - [p81]Francisco Zapata, Eric Smith, Vladik Kreinovich:
Unexpected Economic Consequence of Cloud Computing: A Boost to Algorithmic Creativity. Uncertainty, Constraints, and Decision Making 2023: 301-304 - [p80]Francisco Zapata, Eric Smith, Vladik Kreinovich:
Unreachable Statements Are Inevitable in Software Testing: Theoretical Explanation. Uncertainty, Constraints, and Decision Making 2023: 305-309 - [p79]Barnabás Bede, Marina Tuyako Mizukoshi, Martine Ceberio, Vladik Kreinovich, Weldon A. Lodwick:
Why Constraint Interval Arithmetic Techniques Work Well: A Theorem Explains Empirical Success. Uncertainty, Constraints, and Decision Making 2023: 313-322 - [p78]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
How to Describe Relative Approximation Error? A New Justification for Gustafson's Logarithmic Expression. Uncertainty, Constraints, and Decision Making 2023: 323-327 - [p77]Martine Ceberio, Vladik Kreinovich:
Search Under Uncertainty Should be Randomized: A Lesson from the 2021 Nobel Prize in Medicine. Uncertainty, Constraints, and Decision Making 2023: 329-334 - [p76]Kelly Cohen
, Olga Kosheleva, Vladik Kreinovich:
Why Convex Combination is an Effective Crossover Operation in Continuous Optimization: A Theoretical Explanation. Uncertainty, Constraints, and Decision Making 2023: 335-340 - [p75]Siyu Deng, K. C. Bimal, Vladik Kreinovich:
Why Optimization Is Faster Than Solving Systems of Equations: A Qualitative Explanation. Uncertainty, Constraints, and Decision Making 2023: 341-344 - [p74]Juan Carlos Figueroa García, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Estimating Skewness and Higher Central Moments of an Interval-Valued Fuzzy Set. Uncertainty, Constraints, and Decision Making 2023: 345-352 - [p73]Eric Freudenthal, Olga Kosheleva, Vladik Kreinovich:
How to Detect the Fundamental Frequency: Approach Motivated by Soft Computing and Computational Complexity. Uncertainty, Constraints, and Decision Making 2023: 353-361 - [p72]Olga Kosheleva, Vladik Kreinovich:
What if There Are Too Many Outliers? Uncertainty, Constraints, and Decision Making 2023: 363-370 - [p71]Vladik Kreinovich, Saeid Tizpaz-Niari:
What Is a Natural Probability Distribution on the Class of All Continuous Functions: Maximum Entropy Approach Leads to Wiener Measure. Uncertainty, Constraints, and Decision Making 2023: 371-375 - [p70]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
An Argument in Favor of Piecewise-Constant Membership Functions. Uncertainty, Constraints, and Decision Making 2023: 377-386 - [p69]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Data Processing Under Fuzzy Uncertainty: Towards More Accurate Algorithms. Uncertainty, Constraints, and Decision Making 2023: 387-399 - [p68]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Epistemic Versus Aleatory: Case of Interval Uncertainty. Uncertainty, Constraints, and Decision Making 2023: 401-421 - [p67]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Vladik Kreinovich:
Standard Interval Computation Algorithm Is Not Inclusion-Monotonic: Examples. Uncertainty, Constraints, and Decision Making 2023: 423-440 - [p66]Irina Perfilieva, Vladik Kreinovich:
Monotonic Bit-Invariant Permutation-Invariant Metrics on the Set of All Infinite Binary Sequences. Uncertainty, Constraints, and Decision Making 2023: 441-450 - [p65]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
Computing the Range of a Function-of-Few-Linear-Combinations Under Linear Constraints: A Feasible Algorithm. Uncertainty, Constraints, and Decision Making 2023: 451-457 - [p64]Leobardo Valera, Martine Ceberio, Vladik Kreinovich:
How to Select a Representative Sample for a Family of Functions? Uncertainty, Constraints, and Decision Making 2023: 459-466 - [e21]Martine Ceberio, Vladik Kreinovich:
Decision Making Under Uncertainty and Constraints - A Why-Book. Springer 2023, ISBN 978-3-031-16414-9 [contents] - [e20]Martine Ceberio, Vladik Kreinovich:
Uncertainty, Constraints, and Decision Making. Studies in Systems, Decision and Control 484, Springer 2023, ISBN 978-3-031-36393-1 [contents] - [e19]Scott Dick, Vladik Kreinovich, Pawan Lingras:
Applications of Fuzzy Techniques - Proceedings of the 2022 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2022, Halifax, NS, Canada, 31 May - 3 June 2022. Lecture Notes in Networks and Systems 500, Springer 2023, ISBN 978-3-031-16037-0 [contents] - [e18]Kelly Cohen, Nicholas Ernest, Barnabás Bede, Vladik Kreinovich:
Fuzzy Information Processing 2023 - Proceedings of the 2023 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2023, and at the related Workshop on Constraint Programming and Decision Making CoProD 2023, Cincinnati, OH, USA, May 31 - June 2, 2023. Lecture Notes in Networks and Systems 751, Springer 2023, ISBN 978-3-031-46777-6 [contents] - 2022
- [b5]Julio C. Urenda, Vladik Kreinovich:
Algebraic Approach to Data Processing - Techniques and Applications. Springer 2022, ISBN 978-3-031-16779-9, pp. 1-242 - [b4]Vladik Kreinovich:
Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques. Studies in Computational Intelligence 1047, Springer 2022, ISBN 978-3-031-09973-1, pp. 1-84 - [j428]Javier Viaña
, Stephan Ralescu, Kelly Cohen, Vladik Kreinovich, Anca L. Ralescu:
Why Cauchy Membership Functions: Reliability. Adv. Artif. Intell. Mach. Learn. 2(2) (2022) - [j427]Edgar Daniel Rodriguez Velasquez, Olga Kosheleva, Vladik Kreinovich:
Invariance-Based Approach Explains Empirical Formulas from Pavement Engineering to Deep Learning. Adv. Artif. Intell. Mach. Learn. 2(3): 456-468 (2022) - [j426]Ander Gray
, Scott Ferson
, Vladik Kreinovich
, Edoardo Patelli
:
Distribution-free risk analysis. Int. J. Approx. Reason. 146: 133-156 (2022) - [j425]Vladik Kreinovich, Oscar Galindo, Olga Kosheleva:
Many Known Quantum Algorithms Are Optimal: Symmetry-Based Proofs. Int. J. Comput. 21(4): 411-423 (2022) - [j424]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 30(2): 335-336 (2022) - [j423]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 30(6): 1089-1090 (2022) - [j422]Vladik Kreinovich
:
Ordered Weighted Averaging (OWA), Decision Making under Uncertainty, and Deep Learning: How Is This All Related? Inf. 13(2): 82 (2022) - [j421]Ildar Z. Batyrshin, Fernando A. C. Gomide, Vladik Kreinovich, Shahnaz N. Shahbazova:
Soft computing and advances in intelligent systems. J. Intell. Fuzzy Syst. 43(6): 6895-6896 (2022) - [j420]Solymar Ayala Cortez, Laxman Bokati
, Aaron Velasco
, Vladik Kreinovich:
Why Daubechies wavelets are so successful. J. Intell. Fuzzy Syst. 43(6): 6933-6938 (2022) - [j419]Jonatan M. Contreras, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why neural networks in the first place: a theoretical explanation. J. Intell. Fuzzy Syst. 43(6): 6947-6951 (2022) - [j418]Nancy Solis García, José Guadalupe Flores Muñiz
, Vladik Kreinovich, Nataliya I. Kalashnykova, Viacheslav Kalashnikov:
Consistent Conjectural Variations Equilibrium for a Financial Model. J. Optim. Theory Appl. 194(3): 966-987 (2022) - [j417]Vladik Kreinovich, Olga Kosheleva:
How to Take All Available Information into Account in Fuzzy Decision Making: Beyond Traditional "And" - and "Or" - Operations. J. Multiple Valued Log. Soft Comput. 39(5-6): 445-462 (2022) - [j416]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
When is deep learning better and when is shallow learning better: qualitative analysis. Int. J. Parallel Emergent Distributed Syst. 37(5): 589-595 (2022) - [j415]Vladik Kreinovich:
Min and Max are the Only Continuous $\&$- and $\vee$-Operations for Finite Logics. TFSS 1(1): 170-180 (2022) - [c282]Hung T. Nguyen, Olga Kosheleva, Vladik Kreinovich:
Data Processing under Fuzzy Uncertainty: Towards More Efficient Algorithms. FUZZ-IEEE 2022: 1-7 - [c281]Olga Kosheleva
, Vladik Kreinovich
:
Why People Tend to Overestimate Joint Probabilities. IPMU (1) 2022: 485-493 - [c280]Sean R. Aguilar, Vladik Kreinovich:
Why Best-Worst Method Works Well. IS 2022: 1-4 - [c279]Laxman Bokati
, Vladik Kreinovich:
Why Smaller-Size Objects Affect the Flow Much More than Larger Ones: A Geometric Explanation with Applications Ranging from Volcanoes and Tornadoes to Blood, Fish, and Buildings Preservation. IS 2022: 1-4 - [c278]Laxman Bokati
, Vladik Kreinovich:
Why Exponential Almon Lag Works Well in Econometrics: An Invariance-Based Explanation. IS 2022: 1-4 - [c277]Olga Kosheleva, Vladik Kreinovich:
Invariance Explains Empirical Success of Many Intelligent Techniques. IS 2022: 1-8 - [c276]Vladik Kreinovich:
How to Describe Variety of a Probability Distribution: A Possible Answer to Yager's Question. IS 2022: 1-4 - [c275]Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich:
Why 1/(1+d) Is an Effective Distance-Based Similarity Measure: Two Explanations. IS 2022: 1-6 - [c274]Francisco Zapata, Eric Smith, Olga Kosheleva, Vladik Kreinovich:
Seemingly Counter-Intuitive Features of Good-to-Great Companies Actually Make Perfect Sense: Possible Algorithmics-Based Explanations. IS 2022: 1-4 - [c273]Victor L. Timchenko, Yuriy P. Kondratenko, Vladik Kreinovich:
Decision Support System for the Safety of Ship Navigation Based on Optical Color Logic Gates. IT&I 2022: 42-52 - [c272]Laxman Bokati
, Olga Kosheleva, Vladik Kreinovich:
How to Elicit Complex-Valued Fuzzy Degrees. NAFIPS 2022: 1-11 - [c271]Sofia Holguin, Javier Viaña
, Kelly Cohen
, Anca L. Ralescu, Vladik Kreinovich:
Why Sine Membership Functions. NAFIPS 2022: 83-89 - [c270]Olga Kosheleva, Vladik Kreinovich:
Commonsense-Continuous Dynamical Systems - Stationary States, Prediction, and Reconstruction of the Past: Fuzzy-Based Analysis. NAFIPS 2022: 101-107 - [c269]Chon Van Le, Olga Kosheleva, Vladik Kreinovich:
Why Gaussian Copulas Are Ubiquitous in Economics: Fuzzy-Related Explanation. NAFIPS 2022: 108-112 - [c268]Miroslav Svítek, Vladik Kreinovich:
Why Ideas First Appear in Informal Form? Why It Is Very Difficult to Know Yourself? Fuzzy-Based Explanation. NAFIPS 2022: 279-285 - [c267]Javier Viaña
, Stephan Ralescu
, Vladik Kreinovich
, Anca L. Ralescu
, Kelly Cohen
:
Single Hidden Layer CEFYDRA: Cluster-first Explainable FuzzY-based Deep self-Reorganizing Algorithm. NAFIPS 2022: 298-307 - [c266]Javier Viaña
, Stephan Ralescu
, Vladik Kreinovich
, Anca L. Ralescu
, Kelly Cohen
:
Multiple Hidden Layered CEFYDRA: Cluster-First Explainable Fuzzy-Based Deep Self-reorganizing Algorithm. NAFIPS 2022: 308-322 - [c265]Javier Viaña
, Stephan Ralescu
, Vladik Kreinovich
, Anca L. Ralescu
, Kelly Cohen
:
Initialization and Plasticity of CEFYDRA: Cluster-first Explainable FuzzY-based Deep self-Reorganizing Algorithm. NAFIPS 2022: 323-335 - [c264]Olga Kosheleva
, Vladik Kreinovich
:
Need for Techniques Intermediate Between Interval and Probabilistic Ones. PPAM (2) 2022: 405-414 - [e17]Julia Rayz, Victor Raskin, Scott Dick, Vladik Kreinovich:
Explainable AI and Other Applications of Fuzzy Techniques - Proceedings of the 2021 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2021, Virtual Event / West Lafayette, IN, USA, June 7-9, 2021. Lecture Notes in Networks and Systems 258, Springer 2022, ISBN 978-3-030-82098-5 [contents] - [e16]Barnabás Bede, Martine Ceberio, Martine De Cock, Vladik Kreinovich:
Fuzzy Information Processing 2020 - Proceedings of the 2020 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2020, Redmond, WA, USA, 20-22 August 2020. Advances in Intelligent Systems and Computing 1337, Springer 2022, ISBN 978-3-030-81560-8 [contents] - [i5]Orsolya Csiszár, Luca Sára Pusztaházi, Lehel Dénes-Fazakas, Michael S. Gashler, Vladik Kreinovich, Gábor Csiszár:
Uninorm-like parametric activation functions for human-understandable neural models. CoRR abs/2205.06547 (2022) - [i4]Evgeny Dantsin, Vladik Kreinovich, Alexander Wolpert:
An AlphaZero-Inspired Approach to Solving Search Problems. CoRR abs/2207.00919 (2022) - 2021
- [j414]Juan Carlos Figueroa García, Vladik Kreinovich:
How Accurate Are Fuzzy Control Recommendations: Interval-Valued Case. Adv. Artif. Intell. Mach. Learn. 1(1): 12-25 (2021) - [j413]Javier Viaña
, Stephan Ralescu, Kelly Cohen
, Vladik Kreinovich, Anca L. Ralescu:
Why Cauchy Membership Functions: Efficiency. Adv. Artif. Intell. Mach. Learn. 1(1): 82-89 (2021) - [j412]Ildar Z. Batyrshin, Nailya I. Kubysheva
, Venera Bayrasheva, Olga Kosheleva, Vladik Kreinovich:
Negations of Probability Distributions: A Survey. Computación y Sistemas 25(4) (2021) - [j411]Vladik Kreinovich
, Olga Kosheleva
:
Limit Theorems as Blessing of Dimensionality: Neural-Oriented Overview. Entropy 23(5): 501 (2021) - [j410]Jonatan M. Contreras, Martine Ceberio, Vladik Kreinovich
:
Why Dilated Convolutional Neural Networks: A Proof of Their Optimality. Entropy 23(6): 767 (2021) - [j409]Edgar Daniel Rodriguez Velasquez
, Vladik Kreinovich, Olga Kosheleva:
Invariance-based approach: general methods and pavement engineering case study. Int. J. Gen. Syst. 50(6): 672-702 (2021) - [j408]Olga Kosheleva, Vladik Kreinovich:
Joseph Henrich, The WEIRDest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous, Farrar, Straus, and Giroux, New York, 2020. J. Intell. Fuzzy Syst. 40(1): 1713-1714 (2021) - [j407]Olga Kosheleva, Vladik Kreinovich:
Hung T. Nguyen, Carol L. Walker, and Elbert A. Walker A First Course in Fuzzy Logic (4th edition) CRC Press, Taylor & Francis Book, Boca Raton, Florida, 2019. J. Intell. Fuzzy Syst. 40(1): 1715-1716 (2021) - [j406]Vladik Kreinovich:
Witold Pedrycz An Introduction to Computing with Fuzzy Sets: Analysis, Design, and Applications Springer, Cham, Switzerland, 2021. J. Intell. Fuzzy Syst. 40(1): 1717-1719 (2021) - [j405]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Amanda Jansen, Rough Draft Math: Revising to Learn, Stenhouse Publishers, Portsmouth, New Hampshire, 2020. J. Intell. Fuzzy Syst. 40(2): 3813-3814 (2021) - [j404]Vladik Kreinovich:
Jozo Dujmović, Soft Computing Evaluation Logic: The LSP Decision Method, and Its Applications, IEEE Press and Wiley, Hoboken, New Jersey, 2018. J. Intell. Fuzzy Syst. 40(2): 3815-3817 (2021) - [j403]Vladik Kreinovich:
Boris Kovalerchuk, Visual Knowledge Discovery and Machine Learning Springer, Cham, Switzerland, 2018. J. Intell. Fuzzy Syst. 40(3): 5753-5755 (2021) - [j402]Vladik Kreinovich:
Fabio Cuzzolin, The Geometry of Uncertainty: The Geometry of Imprecise Probabilities Springer, Cham, Switzerland, 2021. J. Intell. Fuzzy Syst. 40(3): 5757-5758 (2021) - [j401]Vladik Kreinovich:
Olga Kosheleva and Karen Villaverde How Interval and Fuzzy Techniques Can Improve Teaching Springer, Cham, Switzerland, 2018. J. Intell. Fuzzy Syst. 40(5): 10323-10324 (2021) - [j400]Olga Kosheleva, Vladik Kreinovich:
Wolfram Eilenberger Time of the Magicians: Wittgenstein, Benjamin, Cassirer, Heidegger, and The Decade that Reinvented Philosophy Penguin Press, New York, 2020. J. Intell. Fuzzy Syst. 40(5): 10325-10327 (2021) - [j399]Olga Kosheleva, Vladik Kreinovich:
Djuro G. Zrilic Functional Processing of Delta-Sigma Bit-Stream, Springer, Cham, Switzerland, 2020. J. Intell. Fuzzy Syst. 40(5): 10329-10330 (2021) - [j398]Vladik Kreinovich:
Concha Bielza and Pedro Larrañaga, Data-Driven Computational Neuroscience: Machine Learning and Statistical Models, Cambridge University Press, Cambridge, UK, 2021. J. Intell. Fuzzy Syst. 41(1): 2513-2514 (2021) - [j397]Vladik Kreinovich:
Chiara Marletto, The Science of Can and Can't: A Physicist's Journey Through the Land of Counterfactuals, Viking, New York, 2021. J. Intell. Fuzzy Syst. 41(1): 2515-2517 (2021) - [j396]Vladik Kreinovich:
Jose Maria Alonso Moral, Ciro Castiello, Luis Magdalena, and Corrado Mencar, Explainable Fuzzy Systems: Paving the Way from Interpretable Fuzzy Systems to Explainable AI Systems, Springer, Cha... J. Intell. Fuzzy Syst. 41(1): 2519-2520 (2021) - [j395]Hung T. Nguyen, Vladik Kreinovich:
Special issue on soft computing in economic application. Soft Comput. 25(12): 7693-7694 (2021) - [c263]Laxman Bokati
, Olga Kosheleva, Vladik Kreinovich:
How Much for a Set: General Case of Decision Making Under Set-Valued Uncertainty. NAFIPS 2021: 52-61 - [c262]Kelly Cohen
, Laxman Bokati
, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why Fuzzy Techniques in Explainable AI? Which Fuzzy Techniques in Explainable AI? NAFIPS 2021: 74-78 - [c261]Olga Kosheleva, Vladik Kreinovich:
A Natural Formalization of Changing-One's-Mind Leads to Square Root of "Not" and to Complex-Valued Fuzzy Logic. NAFIPS 2021: 190-195 - [c260]Olga Kosheleva, Vladik Kreinovich:
Each Realistic Continuous Functional Dependence Implies a Relation Between Some Variables: A Theoretical Explanation of a Fuzzy-Related Empirical Phenomenon. NAFIPS 2021: 196-202 - [c259]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
What Teachers Can Learn from Machine Learning. NAFIPS 2021: 400-405 - [c258]Julio C. Urenda, Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Mexican Folk Arithmetic Algorithm Makes Perfect Sense. NAFIPS 2021: 453-460 - [c257]Francisco Zapata, Olga Kosheleva, Vladik Kreinovich:
Fuzzy Logic Leads to a More Adequate Way of Processing Likert-Scale Values: Case Study of Burnout. NAFIPS 2021: 499-504 - [c256]Michael Beer
, Olga Kosheleva, Vladik Kreinovich:
Uncertainty: Ideas Behind Neural Networks Lead Us Beyond KL- Decomposition and Interval Fields. SSCI 2021: 1-7 - [c255]Ander Gray, Scott Ferson
, Olga Kosheleva, Vladik Kreinovich:
While, In General, Uncertainty Quantification (UQ) Is NP-Hard, Many Practical UQ Problems Can Be Made Feasible. SSCI 2021: 1-6 - [p63]Vladik Kreinovich, Olga Kosheleva, Michael Zakharevich:
Z-Numbers: How They Describe Student Confidence and How They Can Explain (and Improve) Laplacian and Schroedinger Eigenmap Dimension Reduction in Data Analysis. Fuzzy Approaches for Soft Computing and Approximate Reasoning 2021: 285-297 - 2020
- [b3]Griselda Acosta, Eric Smith, Vladik Kreinovich:
Towards Analytical Techniques for Systems Engineering Applications. Springer 2020, ISBN 978-3-030-46412-7, pp. 1-95 - [j394]Ricardo Alvarez, Nick Sims, Christian Servin, Martine Ceberio, Vladik Kreinovich:
If Space-Time Is Discrete, It Could Be Possible to Solve NP-Complete Problems in Polynomial Time. Int. J. Unconv. Comput. 15(3): 193-218 (2020) - [j393]Hung T. Nguyen, Vladik Kreinovich:
Uncertainty Analysis in Economics and Finance: Preface to the Special Issue. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 28(Supplement-1) (2020) - [j392]Hoang Phuong Nguyen
, Vladik Kreinovich:
Towards Making Fuzzy Techniques More Adequate for Combining Knowledge of Several Experts. J. Adv. Comput. Intell. Intell. Informatics 24(5): 583-588 (2020) - [j391]Hoang Phuong Nguyen
, Laxman Bokati
, Vladik Kreinovich:
A New (Simplified) Derivation of Nash's Bargaining Solution. J. Adv. Comput. Intell. Intell. Informatics 24(5): 589-592 (2020) - [j390]Olga Kosheleva, Vladik Kreinovich, Hoang Phuong Nguyen
:
How to Describe Conditions Like 2-out-of-5 in Fuzzy Logic: A Neural Approach. J. Adv. Comput. Intell. Intell. Informatics 24(5): 593-598 (2020) - [j389]Laxman Bokati
, Hoang Phuong Nguyen
, Olga Kosheleva, Vladik Kreinovich:
How to Combine (Dis)Utilities of Different Aspects into a Single (Dis)Utility Value, and How This Is Related to Geometric Images of Happiness. J. Adv. Comput. Intell. Intell. Informatics 24(5): 599-603 (2020) - [j388]Vladik Kreinovich, Omar Masmali, Hoang Phuong Nguyen
, Omar Badreddin:
Theoretical Explanation of Recent Empirically Successful Code Quality Metrics. J. Adv. Comput. Intell. Intell. Informatics 24(5): 604-608 (2020) - [j387]Vladik Kreinovich:
Review of the book John Kay and Mervyn King, Radical Uncertainty: Decision Making Beyond the Numbers, W. W. Norton and Co., New York, 2020. J. Intell. Fuzzy Syst. 39(3): 4803-4805 (2020) - [j386]Vladik Kreinovich:
Review of the Book "Mind in Motion: How Action Shapes Thought" by Barbara Tversky, Basic Books, New York, 2019. J. Intell. Fuzzy Syst. 39(3): 4807-4810 (2020) - [c254]Olga Kosheleva
, Vladik Kreinovich
:
Relativistic Effects Can Be Used to Achieve a Universal Square-Root (Or Even Faster) Computation Speedup. Fields of Logic and Computation III 2020: 179-189 - [c253]Vladik Kreinovich:
Formal Concept Analysis Techniques Can Help in Intelligent Control, Deep Learning, etc. CLA 2020: 9-17 - [c252]Vladik Kreinovich, Martine Ceberio, Olga Kosheleva:
White- and Black-Box Computing and Measurements Under Limited Resources: Cloud, High Performance, and Quantum Computing, and Two Case Studies - Robotic Boat and Hierarchical Covid Testing. ICTES 2020: 1-18 - [c251]Michael Beer
, Julio C. Urenda
, Olga Kosheleva
, Vladik Kreinovich
:
Why Spiking Neural Networks Are Efficient: A Theorem. IPMU (1) 2020: 59-69 - [c250]Michael Beer
, Julio C. Urenda
, Olga Kosheleva
, Vladik Kreinovich
:
Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria. IPMU (1) 2020: 70-79 - [c249]Laxman Bokati
, Olga Kosheleva, Vladik Kreinovich, Uram Anibal Sosa Aguirre:
Why Deep Learning Is More Efficient than Support Vector Machines, and How it is Related to Sparsity Techniques in Signal Processing. ISMSI 2020: 8-12 - [c248]Vladik Kreinovich, Olga Kosheleva:
Deep Learning (Partly) Demystified. ISMSI 2020: 30-35 - [c247]Jonatan M. Contreras, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich, Martine Ceberio:
Let Us Use Negative Examples in Regression-Type Problems Too. IV 2020: 296-300 - [c246]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Adversarial Teaching Approach to Cybersecurity: A Mathematical Model Explains Why It Works Well. IV 2020: 313-316 - [c245]Oscar Galindo, Olga Kosheleva
, Vladik Kreinovich
:
Why Majority Rule Does Not Work in Quantum Computing: A Pedagogical Explanation. MICAI (1) 2020: 396-401 - [c244]Edgar Daniel Rodriguez Velasquez
, Olga Kosheleva
, Vladik Kreinovich
:
How to Decide Which Cracks Should Be Repaired First: Theoretical Explanation of Empirical Formulas. MICAI (1) 2020: 402-410 - [c243]Ricardo Alvarez, Nick Sims, Christian Servin, Martine Ceberio, Vladik Kreinovich:
How to Reconcile Randomness with Physicists' Belief that Every Theory Is Approximate: Informal Knowledge Is Needed. NAFIPS 2020: 373-378 - [c242]Laxman Bokati
, Aaron Velasco, Vladik Kreinovich:
Scale-Invariance and Fuzzy Techniques Explain the Empirical Success of Inverse Distance Weighting and of Dual Inverse Distance Weighting in Geosciences. NAFIPS 2020: 379-390 - [c241]Christian Servin, Vladik Kreinovich:
Is There a Contradiction Between Statistics and Fairness: From Intelligent Control to Explainable AI. NAFIPS 2020: 391-400 - [c240]Olga Kosheleva, Vladik Kreinovich:
Which Algorithms Are Feasible and Which Are Not: Fuzzy Techniques Can Help in Formalizing the Notion of Feasibility. NAFIPS 2020: 401-406 - [c239]Juan Carlos Figueroa García, Christian Servin, Vladik Kreinovich:
Centroids Beyond Defuzzification. NAFIPS 2020: 407-412 - [c238]Leobardo Valera, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Equations for Which Newton's Method Never Works: Pedagogical Examples. NAFIPS 2020: 413-419 - [c237]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Optimal Search Under Constraints. NAFIPS 2020: 421-426 - [c236]Julio C. Urenda, Manuel Hernandez, Natalia Villanueva-Rosales, Vladik Kreinovich:
How User Ratings Change with Time: Theoretical Explanation of an Empirical Formula. NAFIPS 2020: 427-432 - [c235]Julio C. Urenda, Vladik Kreinovich:
Why a Classification Based on Linear Approximation to Dynamical Systems Often Works Well in Nonlinear Cases. NAFIPS 2020: 433-437 - [c234]Julio C. Urenda, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
How Mathematics and Computing Can Help Fight the Pandemic: Two Pedagogical Examples. NAFIPS 2020: 439-442 - [c233]Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Vladik Kreinovich:
Natural Invariance Explains Empirical Success of Specific Membership Functions, Hedge Operations, and Negation Operations. NAFIPS 2020: 443-456 - [c232]Julio C. Urenda
, Orsolya Csiszár, Gábor Csiszár, József Dombi, Olga Kosheleva, Vladik Kreinovich, György Eigner:
Why Squashing Functions in Multi-Layer Neural Networks. SMC 2020: 1705-1711 - [c231]Edgar Daniel Rodriguez Velasquez
, Vladik Kreinovich:
Scale-Invariance Ideas Explain the Empirical Soil-Water Characteristic Curve. SSCI 2020: 958-962 - [c230]Oscar Galindo, Vladik Kreinovich:
What Is the Optimal Annealing Schedule in Quantum Annealing. SSCI 2020: 963-967 - [c229]Deepak K. Tosh
, Oscar Galindo, Vladik Kreinovich, Olga Kosheleva:
Towards Security of Cyber-Physical Systems using Quantum Computing Algorithms. SoSE 2020: 313-320 - [p62]Mahdokht Afravi, Vladik Kreinovich:
Fuzzy Systems Are Universal Approximators for Random Dependencies: A Simplified Proof. Decision Making under Constraints 2020: 1-5 - [p61]Christian Ayub, Martine Ceberio, Vladik Kreinovich:
How Quantum Computing Can Help with (Continuous) Optimization. Decision Making under Constraints 2020: 7-14 - [p60]Chitta Baral, Martine Ceberio, Vladik Kreinovich:
How Neural Networks (NN) Can (Hopefully) Learn Faster by Taking into Account Known Constraints. Decision Making under Constraints 2020: 15-20 - [p59]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Italian Folk Multiplication Algorithm Is Indeed Better: It Is More Parallelizable. Decision Making under Constraints 2020: 59-64 - [p58]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Reverse Mathematics Is Computable for Interval Computations. Decision Making under Constraints 2020: 65-70 - [p57]Angel F. Garcia Contreras, Martine Ceberio, Vladik Kreinovich:
Plans Are Worthless but Planning Is Everything: A Theoretical Explanation of Eisenhower's Observation. Decision Making under Constraints 2020: 93-98 - [p56]Angel F. Garcia Contreras, Martine Ceberio, Vladik Kreinovich:
Why Convex Optimization Is Ubiquitous and Why Pessimism Is Widely Spread. Decision Making under Constraints 2020: 99-104 - [p55]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Attraction-Repulsion Forces Between Biological Cells: A Theoretical Explanation of Empirical Formulas. Decision Making under Constraints 2020: 139-144 - [p54]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
When We Know the Number of Local Maxima, Then We Can Compute All of Them. Decision Making under Constraints 2020: 145-151 - [p53]Andrzej Pownuk, Vladik Kreinovich:
Which Value $\widetilde{x}$ Best Represents a Sample x1, ... , xn: Utility-Based Approach Under Interval Uncertainty. Decision Making under Constraints 2020: 169-174 - [p52]Andrzej Pownuk, Vladik Kreinovich:
Why Unexpectedly Positive Experiences Make Decision Makers More Optimistic: An Explanation. Decision Making under Constraints 2020: 175-179 - [p51]Leobardo Valera, Martine Ceberio, Vladik Kreinovich:
Why Burgers Equation: Symmetry-Based Approach. Decision Making under Constraints 2020: 211-216 - [p50]Francisco Zapata, Maliheh Zargaran, Vladik Kreinovich:
Working on One Part at a Time Is the Best Strategy for Software Production: A Proof. Decision Making under Constraints 2020: 217-221 - [e15]Martine Ceberio, Vladik Kreinovich:
Decision Making under Constraints. Springer 2020, ISBN 978-3-030-40813-8 [contents] - [e14]Yuriy P. Kondratenko, Vladik Kreinovich, Dan Simon, Yaroslav M. Krainyk:
Proceedings of the 2nd International Workshop on Information-Communication Technologies & Embedded Systems (ICTES 2020) Mykolaiv, Ukraine (online), November 12, 2020., Mykolaiv, Ukraine (online), November 12, 2020. CEUR Workshop Proceedings 2762, CEUR-WS.org 2020 [contents]
2010 – 2019
- 2019
- [j385]Vladik Kreinovich
, Olga Kosheleva
, Songsak Sriboonchitta:
Why Use a Fuzzy Partition in F-Transform? Axioms 8(3): 94 (2019) - [j384]Olga Kosheleva
, Vladik Kreinovich
, Thach Ngoc Nguyen:
Why Triangular Membership Functions Are Successfully Used in F-Transform Applications: A Global Explanation to Supplement the Existing Local Ones. Axioms 8(3): 95 (2019) - [j383]Ildar Z. Batyrshin, Olga Kosheleva, Vladik Kreinovich, Nailya I. Kubysheva
, Raouf Akhtiamov
:
Contrast Similarity Measures of Fuzzy Sets. Computación y Sistemas 23(4) (2019) - [j382]Vladik Kreinovich:
Acknowledgements to the Referees (2018). Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(1): 171-173 (2019) - [j381]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(2): 351-352 (2019) - [j380]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(3): 513-514 (2019) - [j379]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(4): 691-692 (2019) - [j378]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(5): 879-880 (2019) - [j377]Ildar Z. Batyrshin, Valerie Cross, Vladik Kreinovich, Maria Rifqi:
Special issue on Similarity, Correlation and Association Measures. J. Intell. Fuzzy Syst. 36(4): 2975-2976 (2019) - [j376]Olga Kosheleva, Vladik Kreinovich:
How to Assign Points for Chores. Russ. Digit. Libr. J. 22(6): 759-762 (2019) - [j375]Olga Kosheleva, Vladik Kreinovich, Francisco Zapata:
Egyptian Fractions Re-Revisited. Russ. Digit. Libr. J. 22(6): 763-768 (2019) - [j374]Mourat Tchoshanov, Olga Kosheleva, Vladik Kreinovich:
Anatole France's Statement on Education Transformed into a Theorem. Russ. Digit. Libr. J. 22(6): 769-772 (2019) - [j373]Laxman Bokati, Vyacheslav Kalashnikov, Nataliya I. Kalashnykova, Olga Kosheleva, Vladik Kreinovich:
How to Assign Grades to Tasks so as to Maximize Student Efforts. Russ. Digit. Libr. J. 22(6): 773-779 (2019) - [c228]Thongchai Dumrongpokaphan, Afshin Gholamy, Vladik Kreinovich, Hoang Phuong Nguyen:
Why Hammerstein-Type Block Models Are so Efficient: Case Study of Financial Econometrics. ECONVN 2019: 129-136 - [c227]Thongchai Dumrongpokaphan, Vladik Kreinovich, Songsak Sriboonchitta:
Why Threshold Models: A Theoretical Explanation. ECONVN 2019: 137-145 - [c226]Thach Ngoc Nguyen, Olga Kosheleva, Vladik Kreinovich, Hoang Phuong Nguyen:
Blockchains Beyond Bitcoin: Towards Optimal Level of Decentralization in Storing Financial Data. ECONVN 2019: 163-167 - [c225]Miroslav Svítek
, Olga Kosheleva, Vladik Kreinovich, Thach Ngoc Nguyen:
Why Quantum (Wave Probability) Models Are a Good Description of Many Non-quantum Complex Systems, and How to Go Beyond Quantum Models. ECONVN 2019: 168-175 - [c224]Tran Anh Tuan, Vladik Kreinovich, Thach Ngoc Nguyen:
Decision Making Under Interval Uncertainty: Beyond Hurwicz Pessimism-Optimism Criterion. ECONVN 2019: 176-184 - [c223]Oscar Galindo, Laxman Bokati, Vladik Kreinovich:
Towards a More Efficient Representation of Functions in Quantum and Reversible Computing. EUSFLAT Conf. 2019 - [c222]Oscar Galindo, Vladik Kreinovich:
For Quantum and Reversible Computing, Intervals Are More Appropriate Than General Sets, And Fuzzy Numbers Than General Fuzzy Sets. EUSFLAT Conf. 2019 - [c221]Olga Kosheleva, Vladik Kreinovich:
Physics's Need for Interval Uncertainty and How It Explains Why Physical Space Is (at Least) 3-Dimensional. EUSFLAT Conf. 2019 - [c220]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Luc Longpré:
Between Dog and Wolf: A Continuous Transition from Fuzzy to Probabilistic Estimates. FUZZ-IEEE 2019: 1-5 - [c219]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Luc Longpré:
In Its Usual Formulation, Fuzzy Computation Is, In General, NP-Hard, But a More Realistic Formulation Can Make It Feasible. FUZZ-IEEE 2019: 1-6 - [c218]Oscar Galindo, Olga Kosheleva, Vladik Kreinovich:
High Concentrations Naturally Lead to Fuzzy-Type Interactions and to Gravitational Wave Bursts. FUZZ-IEEE 2019: 1-5 - [c217]Olga Kosheleva, Christian Servin, Vladik Kreinovich:
Why Grade Distribution Is Often Multi-modal: An Uncertainty-Based Explanation. IFSA/NAFIPS 2019: 106-112 - [c216]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
How to Fuse Expert Knowledge: Not Always "And" but a Fuzzy Combination of "And" and "Or". IFSA/NAFIPS 2019: 113-120 - [c215]Francisco Zapata, Olga Kosheleva, Vladik Kreinovich:
Logarithms Are Not Infinity: A Rational Physics-Related Explanation of the Mysterious Statement by Lev Landau. IFSA/NAFIPS 2019: 746-751 - [c214]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Can We Improve the Standard Algorithm of Interval Computation by Taking Almost Monotonicity into Account? IFSA/NAFIPS 2019: 767-778 - [c213]Michal Cerný, Vladik Kreinovich:
How Accurately Can We Determine the Coefficients: Case of Interval Uncertainty. IFSA/NAFIPS 2019: 779-787 - [c212]Juan Carlos Figueroa-García, Carlos Franco, Vladik Kreinovich:
Fuzzy Approach to Optimal Placement of Health Centers. IFSA/NAFIPS 2019: 793-799 - [c211]Leobardo Valera, Martine Ceberio, Vladik Kreinovich:
Derivation of Louisville-Bratu-Gelfand Equation from Shift- or Scale-Invariance. IFSA/NAFIPS 2019: 813-819 - [c210]Christian Servin
, Olga Kosheleva
, Vladik Kreinovich
:
Probability-Based Approach Explains (and Even Improves) Heuristic Formulas of Defuzzification. IUKM 2019: 98-108 - [c209]Bartlomiej Jacek Kubica
, Laxman Bokati
, Olga Kosheleva
, Vladik Kreinovich
:
Softmax and McFadden's Discrete Choice Under Interval (and Other) Uncertainty. PPAM (2) 2019: 364-373 - [c208]Van Nguyen, William Yeoh
, Tran Cao Son, Vladik Kreinovich, Tiep Le:
A Scheduler for Smart Homes with Probabilistic User Preferences. PRIMA 2019: 138-152 - [c207]Oscar Galindo, Christian Ayub, Martine Ceberio, Vladik Kreinovich:
Faster Quantum Alternative to Softmax Selection in Deep Learning and Deep Reinforcement Learning. SSCI 2019: 815-818 - [c206]Vladik Kreinovich, Martine Ceberio, Ricardo Alvarez:
How to Use Quantum Computing to Check Which Inputs Are Relevant: A Proof That Deutsch-Jozsa Algorithm Is, In Effect, the Only Possibility. SSCI 2019: 829-833 - [c205]Edgar Daniel Rodriguez Velasquez
, Carlos M. Chang Albitres, Vladik Kreinovich:
Relationship between Measurement Results and Expert Estimates of Cumulative Quantities, on the Example of Pavement Roughness. SSCI 2019: 882-885 - [p49]Songsak Sriboonchitta, Luc Longpré, Vladik Kreinovich, Thongchai Dumrongpokaphan:
Why the Best Predictive Models Are Often Different from the Best Explanatory Models: A Theoretical Explanation. Structural Changes and their Econometric Modeling 2019: 163-171 - [p48]Nguyen Ngoc Thach, Olga Kosheleva, Vladik Kreinovich, Hoang Phuong Nguyen:
Algorithmic Need for Subcopulas. Structural Changes and their Econometric Modeling 2019: 172-181 - [p47]Edgar Daniel Rodriguez Velasquez
, Carlos M. Chang Albitres, Thach Ngoc Nguyen, Olga Kosheleva, Vladik Kreinovich:
How to Take Expert Uncertainty into Account: Economic Approach Illustrated by Pavement Engineering Applications. Structural Changes and their Econometric Modeling 2019: 182-190 - [p46]Songsak Sriboonchitta, Hung T. Nguyen, Olga Kosheleva, Vladik Kreinovich, Thach Ngoc Nguyen:
Quantum Approach Explains the Need for Expert Knowledge: On the Example of Econometrics. Structural Changes and their Econometric Modeling 2019: 191-199 - [e13]Vladik Kreinovich, Nguyen Ngoc Thach, Nguyen Duc Trung, Dang Van Thanh:
Beyond Traditional Probabilistic Methods in Economics, ECONVN 2019, International Econometric Conference of Vietnam, Ho Chi Minh City, Vietnam, 14-16 January, 2019. Studies in Computational Intelligence 809, Springer 2019, ISBN 978-3-030-04199-1 [contents] - [e12]Ralph Baker Kearfott, Ildar Z. Batyrshin, Marek Z. Reformat, Martine Ceberio, Vladik Kreinovich:
Fuzzy Techniques: Theory and Applications - Proceedings of the 2019 Joint World Congress of the International Fuzzy Systems Association and the Annual Conference of the North American Fuzzy Information Processing Society IFSA/NAFIPS'2019 (Lafayette, Louisiana, USA, June 18-21, 2019). Advances in Intelligent Systems and Computing 1000, Springer 2019, ISBN 978-3-030-21919-2 [contents] - [e11]Vladik Kreinovich, Songsak Sriboonchitta:
Structural Changes and their Econometric Modeling. Studies in Computational Intelligence 808, Springer 2019, ISBN 978-3-030-04262-2 [contents] - 2018
- [b2]Andrew Pownuk
, Vladik Kreinovich:
Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications. Studies in Computational Intelligence 773, Springer 2018, ISBN 978-3-319-91025-3, pp. 1-191 - [j372]Songsak Sriboonchitta, Vladik Kreinovich
:
Why Are FGM Copulas Successful? A Simple Explanation. Adv. Fuzzy Syst. 2018: 5872195:1-5872195:5 (2018) - [j371]Christian Servin, Gerardo Muela, Vladik Kreinovich
:
Fuzzy Analogues of Sets and Functions Can Be Uniquely Determined from the Corresponding Ordered Category: A Theorem. Axioms 7(1): 8 (2018) - [j370]Salem Benferhat
, Vladik Kreinovich, Amélie Levray, Karim Tabia:
Qualitative conditioning in an interval-based possibilistic setting. Fuzzy Sets Syst. 343: 35-49 (2018) - [j369]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 26(1): 167-168 (2018) - [j368]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 26(2): 343-344 (2018) - [j367]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 26(3): 519-520 (2018) - [j366]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 26(4): 693-694 (2018) - [j365]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 26(5): 875-876 (2018) - [j364]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 26(6): 1053-1054 (2018) - [c204]Michael Beer
, Zitong Gong, Ingo Neumann, Songsak Sriboonchitta, Vladik Kreinovich:
What If We Do Not Know Correlations? ECONVN 2018: 78-85 - [c203]Thongchai Dumrongpokaphan, Vladik Kreinovich:
Markowitz Portfolio Theory Helps Decrease Medicines' Side Effect and Speed up Machine Learning. ECONVN 2018: 86-93 - [c202]Vladik Kreinovich, Anh Hoang Ly, Olga Kosheleva, Songsak Sriboonchitta:
Efficient Parameter-Estimating Algorithms for Symmetry-Motivated Models: Econometrics and Beyond. ECONVN 2018: 134-145 - [c201]Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta:
Quantum Ideas in Economics Beyond Quantum Econometrics. ECONVN 2018: 146-151 - [c200]Anh Hoang Ly, Michael Zakharevich, Olga Kosheleva, Vladik Kreinovich:
An Ancient Bankruptcy Solution Makes Economic Sense. ECONVN 2018: 152-160 - [c199]Thach Ngoc Nguyen, Olga Kosheleva, Vladik Kreinovich:
Maximum Entropy Beyond Selecting Probability Distributions. ECONVN 2018: 186-195 - [c198]Martha Osegueda Escobar, Vladik Kreinovich, Thach Ngoc Nguyen:
Is It Legitimate Statistics or Is It Sexism: Why Discrimination Is Not Rational. ECONVN 2018: 235-242 - [c197]Stephen Schön, Gaël Kermarrec, Boris Kargoll
, Ingo Neumann, Olga Kosheleva, Vladik Kreinovich:
Why Student Distributions? Why Matern's Covariance Model? A Symmetry-Based Explanation. ECONVN 2018: 266-275 - [c196]Olga Kosheleva, Vladik Kreinovich:
Measures of Specificity Used in the Principle of Justifiable Granularity: A Theoretical Explanation of Empirically Optimal Selections. FUZZ-IEEE 2018: 1-7 - [c195]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
How to Detect Crisp Sets Based on Subsethood Ordering of Normalized Fuzzy Sets? How to Detect Type-1 Sets Based on Subsethood Ordering of Normalized Interval-Valued Fuzzy Sets? FUZZ-IEEE 2018: 1-10 - [c194]Olga Kosheleva
, Vladik Kreinovich
:
Why Triangular Membership Functions are Often Efficient in F-transform Applications: Relation to Probabilistic and Interval Uncertainty and to Haar Wavelets. IPMU (2) 2018: 127-138 - [c193]Francisco Zapata, Olga Kosheleva, Vladik Kreinovich, Thongchai Dumrongpokaphan:
Do It Today or Do It Tomorrow: Empirical Non-exponential Discounting Explained by Symmetry Ideas. IUKM 2018: 27-38 - [c192]Kittawit Autchariyapanitkul, Olga Kosheleva, Vladik Kreinovich, Songsak Sriboonchitta:
Quantum Econometrics: How to Explain Its Quantitative Successes and How the Resulting Formulas Are Related to Scale Invariance, Entropy, and Fuzziness. IUKM 2018: 264-275 - [c191]Christian Servin, Vladik Kreinovich:
Towards Foundations of Fuzzy Utility: Taking Fuzziness into Account Naturally Leads to Intuitionistic Fuzzy Degrees. NAFIPS 2018: 530-537 - [c190]Francisco Zapata, Vladik Kreinovich:
How to Gauge Repair Risk? NAFIPS 2018: 551-558 - [c189]Oscar Galindo, Vladik Kreinovich, Olga Kosheleva:
Current Quantum Cryptography Algorithm Is Optimal: A Proof. SSCI 2018: 295-300 - [c188]Edgar Daniel Rodriguez Velasquez
, Carlos M. Chang Albitres, Vladik Kreinovich:
Measurement-Type "Calibration" of Expert Estimates Improves Their Accuracy and Their Usability: Pavement Engineering Case Study. SSCI 2018: 301-304 - [c187]Vladik Kreinovich
, Juan Carlos Figueroa-García
:
Optimization Under Fuzzy Constraints: From a Heuristic Algorithm to an Algorithm that Always Converges. WEA (1) 2018: 3-16 - [p45]Thongchai Dumrongpokaphan, Vladik Kreinovich:
Kuznets Curve: A Simple Dynamical System-Based Explanation. Predictive Econometrics and Big Data 2018: 177-181 - [p44]Vladik Kreinovich, Thongchai Dumrongpokaphan:
How to Estimate Statistical Characteristics Based on a Sample: Nonparametric Maximum Likelihood Approach Leads to Sample Mean, Sample Variance, etc. Predictive Econometrics and Big Data 2018: 192-197 - [p43]Vladik Kreinovich, Thongchai Dumrongpokaphan, Hung T. Nguyen, Olga Kosheleva:
How to Gauge Accuracy of Processing Big Data: Teaching Machine Learning Techniques to Gauge Their Own Accuracy. Predictive Econometrics and Big Data 2018: 198-204 - [p42]Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta, Olga Kosheleva:
How Better Are Predictive Models: Analysis on the Practically Important Example of Robust Interval Uncertainty. Predictive Econometrics and Big Data 2018: 205-213 - [p41]Vladik Kreinovich, Songsak Sriboonchitta:
Quantitative Justification for the Gravity Model in Economics. Predictive Econometrics and Big Data 2018: 214-221 - [p40]Songsak Sriboonchitta, Vladik Kreinovich:
A Bad Plan Is Better Than No Plan: A Theoretical Justification of an Empirical Observation. Predictive Econometrics and Big Data 2018: 266-272 - [e10]Ly Hoang Anh, Le Si Dong, Vladik Kreinovich, Nguyen Ngoc Thach:
Econometrics for Financial Applications, ECONVN 2018, International Econometric Conference of Vietnam, Ho Chi Minh, Vietnam, 15-16 January, 2018. Studies in Computational Intelligence 760, Springer 2018, ISBN 978-3-319-73149-0 [contents] - [e9]Lotfi A. Zadeh, Ronald R. Yager, Shahnaz N. Shahbazova, Marek Z. Reformat, Vladik Kreinovich:
Recent Developments and the New Direction in Soft-Computing Foundations and Applications - Selected Papers from the 6th World Conference on Soft Computing, May 22-25, 2016, Berkeley, USA. Studies in Fuzziness and Soft Computing 361, Springer 2018, ISBN 978-3-319-75407-9 [contents] - [e8]Vladik Kreinovich, Songsak Sriboonchitta, Nopasit Chakpitak:
Predictive Econometrics and Big Data. Studies in Computational Intelligence 753, Springer 2018, ISBN 978-3-319-70941-3 [contents] - 2017
- [j363]Vladik Kreinovich:
Why some physicists are excited about the undecidability of the spectral gap problem and why should we. Bull. EATCS 122 (2017) - [j362]Lukás Havrlant, Vladik Kreinovich:
A simple probabilistic explanation of term frequency-inverse document frequency (tf-idf) heuristic (and variations motivated by this explanation). Int. J. Gen. Syst. 46(1): 27-36 (2017) - [j361]Vladik Kreinovich:
What Will Make Computers Faster: An Approach Based on Computational Complexity. Int. J. Unconv. Comput. 13(3): 215-220 (2017) - [j360]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(1): 187-188 (2017) - [j359]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(2): 347-348 (2017) - [j358]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(3): 495-496 (2017) - [j357]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(4): 675- (2017) - [j356]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(5): 851- (2017) - [j355]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(6): 1019- (2017) - [c186]Gerardo Muela, Olga Kosheleva, Vladik Kreinovich, Christian Servin:
It is possible to determine exact fuzzy values based on an ordering of interval-valued or set-valued fuzzy degrees. FUZZ-IEEE 2017: 1-6 - [c185]Vladik Kreinovich:
How to Deal with Uncertainties in Computing: From Probabilistic and Interval Uncertainty to Combination of Different Approaches, with Applications to Engineering and Bioinformatics. ICADIWT 2017: 3-15 - [c184]Hung T. Nguyen, Kittawit Autchariyapanitkul, Vladik Kreinovich:
Fuzzy techniques explain empirical power law governing wars and terrorist attacks. IFSA-SCIS 2017: 1-4 - [c183]Hung T. Nguyen, Kittawit Autchariyapanitkul, Olga Kosheleva, Vladik Kreinovich:
Uncertain information fusion and knowledge integration: How to take reliability into account. IFSA-SCIS 2017: 1-8 - [c182]Gerardo Muela, Vladik Kreinovich, Christian Servin:
Scaling-invariant description of dependence between fuzzy variables: Towards a fuzzy version of copulas. IFSA-SCIS 2017: 1-6 - [c181]Francisco Zapata, Olga Kosheleva, Vladik Kreinovich:
Which material design is possible under additive manufacturing: A fuzzy approach. IFSA-SCIS 2017: 1-5 - [c180]Patricia Melin
, Oscar Castillo
, Andrzej Pownuk, Olga Kosheleva, Vladik Kreinovich:
How to Gauge the Accuracy of Fuzzy Control Recommendations: A Simple Idea. NAFIPS 2017: 287-292 - [c179]Hamza Alkhatib
, Boris Kargoll
, Ingo Neumann, Vladik Kreinovich:
Normalization-Invariant Fuzzy Logic Operations Explain Empirical Success of Student Distributions in Describing Measurement Uncertainty. NAFIPS 2017: 300-306 - [c178]Christian Servin, Gerardo Muela, Vladik Kreinovich:
Can We Detect Crisp Sets Based Only on the Subsethood Ordering of Fuzzy Sets? Fuzzy Sets and/or Crisp Sets Based on Subsethood of Interval-Valued Fuzzy Sets? NAFIPS 2017: 307-312 - [c177]Ligang Sun
, Hani Dbouk, Ingo Neumann, Steffen Schön
, Vladik Kreinovich:
Taking into Account Interval (and Fuzzy) Uncertainty Can Lead to More Adequate Statistical Estimates. NAFIPS 2017: 371-381 - [c176]Bartlomiej Jacek Kubica
, Andrzej Pownuk, Vladik Kreinovich:
What Decision to Make in a Conflict Situation Under Interval Uncertainty: Efficient Algorithms for the Hurwicz Approach. PPAM (2) 2017: 402-411 - [c175]Ludmila Dymova
, Pavel V. Sevastjanov
, Andrzej Pownuk, Vladik Kreinovich:
Practical Need for Algebraic (Equality-Type) Solutions of Interval Equations and for Extended-Zero Solutions. PPAM (2) 2017: 412-421 - [c174]Justin Parra, Olac Fuentes, Elizabeth Anthony, Vladik Kreinovich:
Predicting volcanic eruptions: Case study of rare events in chaotic systems with delay. SMC 2017: 351-356 - [c173]Solymar Ayala Cortez, Aaron Velasco
, Vladik Kreinovich:
Soft computing approach to detecting discontinuities: Seismic analysis and beyond. SMC 2017: 363-366 - [c172]Sergey I. Kumkov
, Vladik Kreinovich, Andrzej Pownuk:
In system identification, interval (and fuzzy) estimates can lead to much better accuracy than the traditional statistical ones: General algorithm and case study. SMC 2017: 367-372 - [c171]Michael Beer
, Zitong Gong, Francisco Alejandro Diaz De la O, Vladik Kreinovich:
How Accurate Are Expert Estimations of Correlation? SSCI 2017: 1-9 - [p39]Songsak Sriboonchitta, Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva:
Robustness as a Criterion for Selecting a Probability Distribution Under Uncertainty. Robustness in Econometrics 2017: 51-68 - [p38]Thongchai Dumrongpokaphan, Vladik Kreinovich:
Why Cannot We Have a Strongly Consistent Family of Skew Normal (and Higher Order) Distributions. Robustness in Econometrics 2017: 69-77 - [p37]Olga Kosheleva, Vladik Kreinovich, Songsak Sriboonchitta:
Econometric Models of Probabilistic Choice: Beyond McFadden's Formulas. Robustness in Econometrics 2017: 79-87 - [p36]Olga Kosheleva, Vladik Kreinovich, Thongchai Dumrongpokaphan:
How to Explain Ubiquity of Constant Elasticity of Substitution (CES) Production and Utility Functions Without Explicitly Postulating CES. Robustness in Econometrics 2017: 89-98 - [p35]Kongliang Zhu, Nantiworn Thianpaen, Vladik Kreinovich:
How to Make Plausibility-Based Forecasting More Accurate. Robustness in Econometrics 2017: 99-110 - [e7]Vladik Kreinovich, Songsak Sriboonchitta, Van-Nam Huynh:
Robustness in Econometrics. Studies in Computational Intelligence 692, 2017, ISBN 978-3-319-50741-5 [contents] - 2016
- [j354]Irina Perfilieva
, Michal Holcapek
, Vladik Kreinovich
:
A new reconstruction from the F-transform components. Fuzzy Sets Syst. 288: 3-25 (2016) - [j353]Vyacheslav Kalashnikov, Vladik Kreinovich, José Guadalupe Flores Muñiz, Nataliya I. Kalashnykova:
Structure of Filled Functions: Why Gaussian and Cauchy Templates Are Most Efficient. Int. J. Comb. Optim. Probl. Informatics 7(3): 87-93 (2016) - [j352]Hung T. Nguyen, Vladik Kreinovich:
Fifty Years of Fuzzy Sets: Contributions to Fuzzy Theory (Preface to the Special Issue). Int. J. Intell. Syst. 31(3): 211-214 (2016) - [j351]Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta:
Need for Data Processing Naturally Leads to Fuzzy Logic (and Neural Networks): Fuzzy Beyond Experts and Beyond Probabilities. Int. J. Intell. Syst. 31(3): 276-293 (2016) - [j350]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 24(1): 165- (2016) - [j349]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 24(2): 325- (2016) - [j348]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 24(3): 479- (2016) - [j347]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 24(4): 629- (2016) - [j346]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 24(5): 805- (2016) - [j345]Rafik A. Aliev, Witold Pedrycz, Vladik Kreinovich, Oleg H. Huseynov
:
The general theory of decisions. Inf. Sci. 327: 125-148 (2016) - [c170]Salem Benferhat
, Amélie Levray, Karim Tabia, Vladik Kreinovich:
Set-Valued Conditioning in a Possibility Theory Setting. ECAI 2016: 604-612 - [c169]Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva:
Membership functions representing a number vs. representing a set: Proof of unique reconstruction. FUZZ-IEEE 2016: 657-662 - [c168]Fernando Cervantes, Bryan Usevitch, Leobardo Valera, Vladik Kreinovich, Olga Kosheleva:
Fuzzy techniques provide a theoretical explanation for the heuristic ℓp-regularization of signals and images. FUZZ-IEEE 2016: 1323-1327 - [c167]Boris Kovalerchuk
, Vladik Kreinovich:
Comparison of formulations of applied tasks with intervals, fuzzy sets and probability approaches. FUZZ-IEEE 2016: 1478-1483 - [c166]Irina Perfilieva
, Michal Holcapek
, Vladik Kreinovich:
Adjoint Fuzzy Partition and Generalized Sampling Theorem. IPMU (2) 2016: 459-469 - [c165]Ildar Z. Batyrshin, Thongchai Dumrongpokaphan, Vladik Kreinovich, Olga Kosheleva:
How to Select an Appropriate Similarity Measure: Towards a Symmetry-Based Approach. IUKM 2016: 457-468 - [c164]Songsak Sriboonchitta, Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen:
Need for Most Accurate Discrete Approximations Explains Effectiveness of Statistical Methods Based on Heavy-Tailed Distributions. IUKM 2016: 523-531 - [c163]Bui Cong Cuong, Vladik Kreinovich, Roan Thi Ngan:
A classification of representable t-norm operators for picture fuzzy sets. KSE 2016: 19-24 - [c162]Vladik Kreinovich, Songsak Sriboonchitta:
For Multi-interval-valued Fuzzy Sets, Centroid Defuzzification Is Equivalent to Defuzzifying Its Interval Hull: A Theorem. MICAI (1) 2016: 211-218 - [c161]Mahdokht Afravi, Vladik Kreinovich, Thongchai Dumrongpokaphan:
Metric Spaces Under Interval Uncertainty: Towards an Adequate Definition. MICAI (1) 2016: 219-227 - [c160]Mahdokht Afravi, Vladik Kreinovich:
What if we use different "and"-operations in the same expert system. NAFIPS 2016: 1-5 - [c159]Martine Ceberio, Vladik Kreinovich:
Greetings from NAFIPS 2016 organizing committee chairs. NAFIPS 2016: 1 - [c158]Fernando Cervantes, Bryan Usevitch, Vladik Kreinovich:
Why ℓp-methods in signal and image processing: A fuzzy-based explanation. NAFIPS 2016: 1-5 - [c157]Olga Kosheleva, Vladik Kreinovich, Martha Osegueda Escobar, Kimberly Kato:
Towards the most robust way of assigning numerical degrees to ordered labels, with possible applications to dark matter and dark energy. NAFIPS 2016: 1-4 - [c156]Pedro Barragan Olague, Olga Kosheleva, Vladik Kreinovich:
How resilient modulus of a pavement depends on moisture level: Towards a theoretical justification of a practically important empirical formula. NAFIPS 2016: 1-4 - [c155]Andrzej Pownuk, Vladik Kreinovich:
Which point from an interval should we choose? NAFIPS 2016: 1-4 - [c154]Olga Kosheleva, Vladik Kreinovich, Joe Lorkowski, Martha Osegueda Escobar:
How to transform partial order between degrees into numerical values. SMC 2016: 2489-2494 - [c153]Fernando Cervantes, Bryan Usevitch, Vladik Kreinovich:
Rotation-invariance can further improve state-of-the-art blind deconvolution techniques. SMC 2016: 2495-2500 - [c152]Olga Kosheleva, Vladik Kreinovich, Martha Osegueda Escobar:
Fuzzy-inspired hierarchical version of the von Neumann-Morgenstern solutions as a natural way to resolve collaboration-related conflicts. SMC 2016: 2511-2515 - [c151]Anthony Welte, Luc Jaulin, Martine Ceberio, Vladik Kreinovich:
Robust data processing in the presence of uncertainty and outliers: Case of localization problems. SSCI 2016: 1-7 - [c150]Nicolás Madrid
, Irina Perfilieva
, Vladik Kreinovich:
How to Describe Measurement Uncertainty and Uncertainty of Expert Estimates? WCSC 2016: 247-257 - [c149]Fernando Cervantes, Bryan Usevitch, Leobardo Valera, Vladik Kreinovich:
Why Sparse? Fuzzy Techniques Explain Empirical Efficiency of Sparsity-Based Data- and Image-Processing Algorithms. WCSC 2016: 419-428 - [c148]Vladik Kreinovich, Olga Kosheleva, Thongchai Dumrongpokaphan:
Beyond Traditional Applications of Fuzzy Techniques: Main Idea and Case Studies. WCSC 2016: 465-481 - [c147]Olga Kosheleva, Vladik Kreinovich, Laécio Carvalho de Barros:
Chemical Kinetics in Situations Intermediate Between Usual and High Concentrations: Fuzzy-Motivated Derivation of the Formulas. WCSC 2016: 525-533 - [c146]Pedro Barragan Olague, Soheil Nazarian, Vladik Kreinovich, Afshin Gholamy, Mehran Mazari
:
How to Estimate Resilient Modulus for Unbound Aggregate Materials: A Theoretical Explanation of an Empirical Formula. WCSC 2016: 571-580 - [c145]Stephen M. Escarzaga, Craig E. Tweedie, Olga Kosheleva, Vladik Kreinovich:
How to Predict Nesting Sites and How to Measure Shoreline Erosion: Fuzzy and Probabilistic Techniques for Environment-Related Spatial Data Processing. WCSC 2016: 595-604 - [p34]Vladik Kreinovich, Andrzej Pownuk, Olga Kosheleva:
Combining Interval and Probabilistic Uncertainty: What Is Computable? Advances in Stochastic and Deterministic Global Optimization 2016: 13-32 - [p33]Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen, Songsak Sriboonchitta:
Across-the-Board Spending Cuts Are Very Inefficient: A Proof. Causal Inference in Econometrics 2016: 109-118 - [p32]Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen, Songsak Sriboonchitta:
Invariance Explains Multiplicative and Exponential Skedactic Functions. Causal Inference in Econometrics 2016: 119-131 - [p31]Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen, Songsak Sriboonchitta:
Why Some Families of Probability Distributions Are Practically Efficient: A Symmetry-Based Explanation. Causal Inference in Econometrics 2016: 133-152 - [p30]Vladik Kreinovich, Bui Cong Cuong:
Fuzzy, Intuitionistic Fuzzy, What Next? Imprecision and Uncertainty in Information Representation and Processing 2016: 3-13 - [e6]Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta:
Causal Inference in Econometrics. Studies in Computational Intelligence 622, Springer 2016, ISBN 978-3-319-27283-2 [contents] - [i3]Vladik Kreinovich, Chitta Baral:
On Selecting a Conjunction Operation in Probabilistic Soft Logic. CoRR abs/1611.06631 (2016) - 2015
- [j344]Michal Holcapek
, Irina Perfilieva
, Vilém Novák, Vladik Kreinovich:
Necessary and sufficient conditions for generalized uniform fuzzy partitions. Fuzzy Sets Syst. 277: 97-121 (2015) - [j343]Vladik Kreinovich, Chrysostomos D. Stylios:
Why Fuzzy Cognitive Maps Are Efficient. Int. J. Comput. Commun. Control 10(6): 65-73 (2015) - [j342]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(1): 147-148 (2015) - [j341]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(2): 317-318 (2015) - [j340]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(3): 481-482 (2015) - [j339]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(4): 649-650 (2015) - [j338]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(5): 805- (2015) - [j337]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(6): 971- (2015) - [j336]Hung T. Nguyen, Vladik Kreinovich:
50 Years of Fuzzy Sets: Preface. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(Supplement-1) (2015) - [j335]Vladik Kreinovich, Rujira Ouncharoen
:
Fuzzy (and Interval) Techniques in the Age of Big Data: An Overview with Applications to Environmental Science, Geosciences, Engineering, and Medicine. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(Supplement-1): 75-90 (2015) - [j334]Meng Yuan, Xu Lin, Junzo Watada, Vladik Kreinovich:
Minimax Portfolio Optimization Under Interval Uncertainty. J. Adv. Comput. Intell. Intell. Informatics 19(5): 575-580 (2015) - [j333]Joe Lorkowski, Olga Kosheleva, Vladik Kreinovich, Sergei Soloviev:
How Design Quality Improves with Increasing Computational Abilities: General Formulas and Case Study of Aircraft Fuel Efficiency. J. Adv. Comput. Intell. Intell. Informatics 19(5): 581-584 (2015) - [j332]Beverly Rivera, Francisco Zapata, Vladik Kreinovich:
Security Risk Assessment: Towards a Justification for the Security Risk Factor Table Model. J. Adv. Comput. Intell. Intell. Informatics 19(5): 676-680 (2015) - [j331]Vladik Kreinovich, Hung T. Nguyen, Olga Kosheleva, Rujira Ouncharoen
:
50 Years of fuzzy: from discrete to continuous to - Where? J. Intell. Fuzzy Syst. 29(3): 989-1009 (2015) - [j330]Rujira Ouncharoen
, Vladik Kreinovich, Hung T. Nguyen:
Why Lattice-valued fuzzy values? A mathematical justification. J. Intell. Fuzzy Syst. 29(4): 1421-1425 (2015) - [c144]Afshin Gholamy, Vladik Kreinovich:
How geophysicists' intuition helps seismic data processing. IFSA-EUSFLAT 2015 - [c143]Olga Kosheleva, Vladik Kreinovich:
Adding possibilistic knowledge to probabilities makes many problems algorithmically decidable. IFSA-EUSFLAT 2015 - [c142]Joe Lorkowski, Olga Kosheleva, Vladik Kreinovich:
How success in a task depends on the skills level: two uncertainty-based justifications of a semi-heuristic Rasch model. IFSA-EUSFLAT 2015 - [c141]Joe Lorkowski, Olga Kosheleva, Vladik Kreinovich:
How to take into account a student's degree of certainty when evaluating the test results. FIE 2015: 1-5 - [c140]Salem Benferhat, Martine Ceberio, Vladik Kreinovich, Sylvain Lagrue, Karim Tabia:
On the Normalization of Interval-Based Possibility Distributions. FLAIRS 2015: 20-25 - [c139]Olga Kosheleva, Craig E. Tweedie, Vladik Kreinovich:
Which bio-diversity indices are most adequate. FUZZ-IEEE 2015: 1-7 - [c138]Hung T. Nguyen, Vladik Kreinovich, Joe Lorkowski, Saiful Abu:
Why Sugeno λ-measures. FUZZ-IEEE 2015: 1-7 - [c137]Christian Servin, Hung T. Nguyen, Vladik Kreinovich:
How to estimate expected shortfall when probabilities are known with interval or fuzzy uncertainty. FUZZ-IEEE 2015: 1-5 - [c136]Anderson Braga de Avila, Murilo Schmalfuss, Renata Reiser
, Vladik Kreinovich:
Fuzzy Xor Classes from Quantum Computing. ICAISC 2015: 305-317 - [c135]Salem Benferhat, Amélie Levray, Karim Tabia, Vladik Kreinovich:
Compatible-Based Conditioning in Interval-Based Possibilistic Logic. IJCAI 2015: 2777-2783 - [c134]Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta, Olga Kosheleva:
Why Copulas Have Been Successful in Many Practical Applications: A Theoretical Explanation Based on Computational Efficiency. IUKM 2015: 112-125 - [c133]Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva, Songsak Sriboonchitta:
Why ARMAX-GARCH Linear Models Successfully Describe Complex Nonlinear Phenomena: A Possible Explanation. IUKM 2015: 138-150 - [c132]Vladik Kreinovich:
Formalizing the informal, precisiating the imprecise: How fuzzy logic can help mathematicians and physicists by formalizing their intuitive ideas. NAFIPS/WConSC 2015: 1 - [c131]Vladik Kreinovich, Jonathan Quijas, Esthela Gallardo, Caio De Sa Lopes, Olga Kosheleva, Shahnaz N. Shahbazova
:
Simple linear interpolation explains all usual choices in fuzzy techniques: Membership functions, t-norms, t-conorms, and defuzzification. NAFIPS/WConSC 2015: 1-5 - [c130]William Melek, Barnabás Bede, Luciano Stefanini
, Vladik Kreinovich, Marek Z. Reformat
:
Greetings. NAFIPS/WConSC 2015: 1 - [c129]Christian Servin, Vladik Kreinovich, Olga Kosheleva:
From 1-D to 2-D fuzzy: A proof that interval-valued and complex-valued are the only distributive options. NAFIPS/WConSC 2015: 1-6 - [c128]Chrysostomos D. Stylios, Vladik Kreinovich:
Symbolic Aggregate approXimation (SAX) under interval uncertainty. NAFIPS/WConSC 2015: 1-7 - [c127]Chrysostomos D. Stylios, Andrzej Pownuk, Vladik Kreinovich:
Sometimes, it is beneficial to process different types of uncertainty separately. NAFIPS/WConSC 2015: 1-5 - [c126]Francisco Zapata, Octavio Lerma, Leobardo Valera, Vladik Kreinovich:
How to speed up software migration and modernization: Successful strategies developed by precisiating expert knowledge. NAFIPS/WConSC 2015: 1-6 - [c125]Vladik Kreinovich, Esthela Gallardo:
Optimizing Cloud Use Under Interval Uncertainty. PPAM (2) 2015: 435-444 - [c124]Martine Ceberio, Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta, Rujira Ouncharoen:
What is the Right Context for an Engineering Problem: Finding Such a Context is NP-Hard. SSCI 2015: 1615-1620 - [c123]Joe Lorkowski, Vladik Kreinovich, Olga Kosheleva:
In Engineering Classes, How to Assign Partial Credit: From Current Subjective Practice to Exact Formulas (Based on Computational Intelligence Ideas). SSCI 2015: 1621-1626 - [p29]Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta:
What if We Only Have Approximate Stochastic Dominance? Econometrics of Risk 2015: 53-61 - [p28]Vladik Kreinovich, Hung T. Nguyen, Rujira Ouncharoen
:
From Mean and Median Income to the Most Adequate Way of Taking Inequality into Account. Econometrics of Risk 2015: 63-73 - [p27]Vladik Kreinovich, Olga Kosheleva:
Is the World Itself Fuzzy? Physical Arguments and Unexpected Computational Consequences of Zadeh's Vision. Fifty Years of Fuzzy Logic and its Applications 2015: 297-313 - [p26]Olga Kosheleva, Renata Reiser
, Vladik Kreinovich:
Formalizing the Informal, Precisiating the Imprecise: How Fuzzy Logic Can Help Mathematicians and Physicists by Formalizing Their Intuitive Ideas. Towards the Future of Fuzzy Logic 2015: 301-321 - [e5]Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta, Komsan Suriya
:
Econometrics of Risk. Studies in Computational Intelligence 583, Springer 2015, ISBN 978-3-319-13448-2 [contents] - 2014
- [j329]Hung T. Nguyen, Vladik Kreinovich:
How to fully represent expert information about imprecise properties in a computer system: random sets, fuzzy sets, and beyond: an overview. Int. J. Gen. Syst. 43(6): 586-609 (2014) - [j328]Vladik Kreinovich:
Dynamic fuzzy logic leads to more adequate 'and' and 'or' operations. Int. J. Knowl. Eng. Soft Data Paradigms 4(4): 327-338 (2014) - [j327]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 22(1): 177- (2014) - [j326]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 22(3): 489- (2014) - [j325]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 22(4): 641- (2014) - [j324]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 22(5): 791- (2014) - [j323]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 22(6): 941- (2014) - [j322]Vilém Novák, Irina Perfilieva
, Michal Holcapek
, Vladik Kreinovich:
Filtering out high frequencies in time series using F-transform. Inf. Sci. 274: 192-209 (2014) - [j321]Andres Ortiz, Vladik Kreinovich:
Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites. Symmetry 6(1): 90-102 (2014) - [c122]Quentin Brefort, Luc Jaulin, Martine Ceberio, Vladik Kreinovich:
If we take into account that constraints are soft, then processing constraints becomes algorithmically solvable. CIES 2014: 1-10 - [c121]Afshin Gholamy, Vladik Kreinovich:
Why Ricker wavelets are successful in processing seismic data: Towards a theoretical explanation. CIES 2014: 11-16 - [c120]Olga Kosheleva, Vladik Kreinovich:
Approximate nature of traditional fuzzy methodology naturally leads to complex-valued fuzzy degrees. FUZZ-IEEE 2014: 1475-1479 - [c119]Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva:
"And"- and "Or"-operations for "double", "triple", etc. fuzzy sets. FUZZ-IEEE 2014: 1765-1771 - [c118]Joe Lorkowski, Vladik Kreinovich, Rafik A. Aliev:
Towards decision making under interval, set-valued, fuzzy, and Z-number uncertainty: A fair price approach. FUZZ-IEEE 2014: 2244-2253 - [c117]Luc Longpré, Olga Kosheleva, Vladik Kreinovich:
Towards the Possibility of Objective Interval Uncertainty. SCAN 2014: 54-65 - [c116]Joe Lorkowski, Vladik Kreinovich:
How Much for an Interval? a Set? a Twin Set? a p-Box? A Kaucher Interval? Towards an Economics-Motivated Approach to Decision Making Under Uncertainty. SCAN 2014: 66-76 - [c115]Karen Richart, Olga Kosheleva, Vladik Kreinovich:
r-bounded fuzzy measures are equivalent to ε-possibility measures. SMC 2014: 1210-1215 - [c114]Christian Servin, Aaron Velasco
, Vladik Kreinovich:
How to estimate relative spatial resolution of different maps or images of the same area? SMC 2014: 3492-3496 - [c113]Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta:
How to Detect Linear Dependence on the Copula Level? TES 2014: 63-79 - [c112]Songsak Sriboonchitta, Jianxu Liu
, Vladik Kreinovich, Hung T. Nguyen:
Vine Copulas As a Way to Describe and Analyze Multi-Variate Dependence in Econometrics: Computational Motivation and Comparison with Bayesian Networks and Fuzzy Approaches. TES 2014: 169-184 - [c111]Songsak Sriboonchitta, Jianxu Liu
, Vladik Kreinovich, Hung T. Nguyen:
A Vine Copula Approach for Analyzing Financial Risk and Co-movement of the Indonesian, Philippine and Thailand Stock Markets. TES 2014: 245-257 - [c110]Jianxu Liu
, Songsak Sriboonchitta, Hung T. Nguyen, Vladik Kreinovich:
Studying Volatility and Dependency of Chinese Outbound Tourism Demand in Singapore, Malaysia, and Thailand: A Vine Copula Approach. TES 2014: 259-274 - [c109]Joe Lorkowski, Vladik Kreinovich:
Fuzzy Logic Ideas Can Help in Explaining Kahneman and Tversky's Empirical Decision Weights. WCSC 2014: 89-98 - [p25]Eduardo Cabral Balreira, Olga Kosheleva, Vladik Kreinovich:
Algorithmics of Checking whether a Mapping Is Injective, Surjective, and/or Bijective. Constraint Programming and Decision Making 2014: 1-7 - [p24]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Simplicity Is Worse Than Theft: A Constraint-Based Explanation of a Seemingly Counter-Intuitive Russian Saying. Constraint Programming and Decision Making 2014: 9-13 - [p23]Martine Ceberio, Vladik Kreinovich:
Continuous If-Then Statements Are Computable. Constraint Programming and Decision Making 2014: 15-18 - [p22]Aline Jaimes, Craig Tweedy, Tanja Magoc, Vladik Kreinovich, Martine Ceberio:
Selecting the Best Location for a Meteorological Tower: A Case Study of Multi-objective Constraint Optimization. Constraint Programming and Decision Making 2014: 61-65 - [p21]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Why Tensors? Constraint Programming and Decision Making 2014: 75-78 - [p20]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Adding Constraints - A (Seemingly Counterintuitive but) Useful Heuristic in Solving Difficult Problems. Constraint Programming and Decision Making 2014: 79-83 - [p19]Vladik Kreinovich:
Under Physics-Motivated Constraints, Generally-Non-Algorithmic Computational Problems become Algorithmically Solvable. Constraint Programming and Decision Making 2014: 85-89 - [p18]Vladik Kreinovich, Juan Ferret, Martine Ceberio:
Constraint-Related Reinterpretation of Fundamental Physical Equations Can Serve as a Built-In Regularization. Constraint Programming and Decision Making 2014: 91-95 - [p17]Paden Portillo, Martine Ceberio, Vladik Kreinovich:
Towards an Efficient Bisection of Ellipsoids. Constraint Programming and Decision Making 2014: 137-141 - [p16]Vladik Kreinovich:
Decision Making Under Interval Uncertainty (and Beyond). Human-Centric Decision-Making Models for Social Sciences 2014: 163-193 - [p15]Uram Anibal Sosa Aguirre, Martine Ceberio, Vladik Kreinovich:
Why Curvature in L-Curve: Combining Soft Constraints. Constraint Programming and Decision Making 2014: 175-179 - [e4]Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta:
Modeling Dependence in Econometrics - Selected Papers of the Seventh International Conference of the Thailand Econometric Society, TES 2014, Faculty of Economics, Chiang Mai University, Thailand, January 8-10, 2014. Advances in Intelligent Systems and Computing 251, Springer 2014, ISBN 978-3-319-03394-5 [contents] - [e3]Mo M. Jamshidi, Vladik Kreinovich, Janusz Kacprzyk:
Advance Trends in Soft Computing - Proceedings of WCSC 2013, December 16-18, San Antonio, Texas, USA. Studies in Fuzziness and Soft Computing 312, Springer 2014, ISBN 978-3-319-03673-1 [contents] - [e2]Martine Ceberio, Vladik Kreinovich:
Constraint Programming and Decision Making. Studies in Computational Intelligence 539, Springer 2014, ISBN 978-3-319-04279-4 [contents] - [i2]Alexander Titovets, Philip Mills, Vladik Kreinovich:
Computers Should Be Uniters Not Dividers: A Vision of Computer-Enhanced Happy Future. CoRR abs/1409.0158 (2014) - 2013
- [j320]Van-Nam Huynh, Vladik Kreinovich:
Uncertainty in financial econometrics: Editorial. Int. J. Approx. Reason. 54(6): 699-700 (2013) - [j319]Gang Xiang, Vladik Kreinovich:
Towards fast and accurate algorithms for processing fuzzy data: interval computations revisited. Int. J. Gen. Syst. 42(2): 197-223 (2013) - [j318]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 21(1): 163- (2013) - [j317]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 21(2): 323- (2013) - [j316]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 21(3): 481- (2013) - [j315]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 21(4): 643- (2013) - [j314]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 21(5): 795- (2013) - [j313]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 21(6): 955- (2013) - [j312]Matthias Stein, Michael Beer
, Vladik Kreinovich:
Bayesian approach for inconsistent information. Inf. Sci. 245: 96-111 (2013) - [j311]Marcin Michalak, Vladik Kreinovich:
Is it Possible to Have a Feasible Enclosure-Computing Method Which Is Independent of the Equivalent Form? Reliab. Comput. 18: 1-8 (2013) - [j310]Andrzej Pownuk, Luc Longpré, Vladik Kreinovich:
Checking Monotonicity is NP-Hard Even for Cubic Polynomials. Reliab. Comput. 18: 90-96 (2013) - [j309]Vladik Kreinovich, Wolfram Luther, Evgenija D. Popova
:
Special issue on "uncertainty modeling and analysis with intervals: foundations, tools, applications". Soft Comput. 17(8): 1315-1317 (2013) - [j308]Michael Beer
, Vladik Kreinovich:
Interval or moments: which carry more information? Soft Comput. 17(8): 1319-1327 (2013) - [j307]Francisco Zapata, Vladik Kreinovich, Cliff A. Joslyn
, Emilie Hogan:
Orders on intervals over partially ordered sets: extending Allen's algebra and interval graph results. Soft Comput. 17(8): 1379-1391 (2013) - [c108]Irina Perfilieva
, Vladik Kreinovich:
F-transform in View of Aggregation Functions. AGOP 2013: 381-389 - [c107]Christopher Kiekintveld, Towhidul Islam, Vladik Kreinovich:
Security games with interval uncertainty. AAMAS 2013: 231-238 - [c106]Vladik Kreinovich:
In the Beginning Was the Word, and the Word Was Fuzzy. On Fuzziness (1) 2013: 337-341 - [c105]Konstantin K. Semenov
, Vladik Kreinovich:
From p-boxes to p-ellipsoids: Towards an optimal representation of imprecise probabilities. CIES 2013: 149-156 - [c104]Gang Xiang, Vladik Kreinovich:
Data anonymization that leads to the most accurate estimates of statistical characteristics. CIES 2013: 163-170 - [c103]Vladik Kreinovich, Irina Perfilieva
, Vilém Novák:
Why inverse F-transform? A compression-based explanation. FUZZ-IEEE 2013: 1-7 - [c102]Renata Hax Sander Reiser
, Adriano Maron, Lidiane Visintin
, Ana Maria Abeijon, Vladik Kreinovich:
Relation between polling and Likert-scale approaches to eliciting membership degrees clarified by quantum computing. FUZZ-IEEE 2013: 1-6 - [c101]Lidiane Visintin
, Adriano Maron, Renata Reiser
, Vladik Kreinovich:
Aggregation operations from quantum computing. FUZZ-IEEE 2013: 1-8 - [c100]Ali Jalal-Kamali, Vladik Kreinovich:
Estimating third central moment C3 for privacy case under interval and fuzzy uncertainty. IFSA/NAFIPS 2013: 454-459 - [c99]Joe Lorkowski, Vladik Kreinovich:
Likert-scale fuzzy uncertainty from a traditional decision making viewpoint: It incorporates both subjective probabilities and utility information. IFSA/NAFIPS 2013: 525-530 - [c98]Olga Kosheleva, Vladik Kreinovich, Thavatchai Ngamsantivong:
Why complex-valued fuzzy? Why complex values in general? A computational explanation. IFSA/NAFIPS 2013: 1233-1236 - [c97]Vladik Kreinovich, Andres Ortiz:
Towards a better understanding of space-time causality: Kolmogorov complexity and causality as a matter of degree. IFSA/NAFIPS 2013: 1349-1353 - [c96]Enrique Portillo, Olga Kosheleva, Vladik Kreinovich:
Towards Discrete Interval, Set, and Fuzzy Computations. SMC 2013: 322-327 - [c95]Vladik Kreinovich, Olga Kosheleva, Jorge Y. Cabrera, Mario Gutiérrez, Thavatchai Ngamsantivong:
A Symmetry-Based Approach to Selecting Membership Functions and Its Relation to Chemical Kinetics. SMC 2013: 339-343 - [c94]Olga Kosheleva, Vladik Kreinovich, Ariel García, Felipe Jovel, Luis A. T. Escobedo, Thavatchai Ngamsantivong:
Computing with Words: Towards a New Tuple-Based Formalization. SMC 2013: 344-349 - [c93]Michal Holcapek
, Vladik Kreinovich:
Processing Quantities with Heavy-Tailed Distribution of Measurement Uncertainty: How to Estimate the Tails of the Results of Data Processing. WCSC 2013: 25-32 - [c92]Olga Kosheleva, Vladik Kreinovich, Thavatchai Ngamsantivong:
Fuzzy Sets Can Be Interpreted as Limits of Crisp Sets, and This Can Help to Fuzzify Crisp Notions. WCSC 2013: 327-337 - [c91]Christian Servin, Aline Jaimes, Craig E. Tweedie, Aaron Velasco
, Omar Ochoa, Vladik Kreinovich:
How to Gauge Accuracy of Measurements and of Expert Estimates: Beyond Normal Distributions. WCSC 2013: 339-346 - [c90]Gözde Ulutagay, Vladik Kreinovich:
Density-Based Fuzzy Clustering as a First Step to Learning Rules: Challenges and Solutions. WCSC 2013: 357-372 - [c89]Joshua Day, Ali Jalal-Kamali, Vladik Kreinovich:
Computing Covariance and Correlation in Optimally Privacy-Protected Statistical Databases: Feasible Algorithms. WCSC 2013: 373-382 - [p14]Christian Servin, Martine Ceberio, Aline Jaimes, Craig E. Tweedie, Vladik Kreinovich:
How to Describe and Propagate Uncertainty When Processing Time Series: Metrological and Computational Challenges, with Potential Applications to Environmental Studies. Time Series Analysis, Modeling and Applications 2013: 279-299 - 2012
- [b1]Hung T. Nguyen, Vladik Kreinovich, Berlin Wu, Gang Xiang:
Computing Statistics under Interval and Fuzzy Uncertainty - Applications to Computer Science and Engineering. Studies in Computational Intelligence 393, Springer 2012 - [j306]Vladik Kreinovich, Monchaya Chiangpradit
, Wararit Panichkitkosolkul:
Efficient algorithms for heavy-tail analysis under interval uncertainty. Ann. Oper. Res. 195(1): 73-96 (2012) - [j305]Jaime Nava, Vladik Kreinovich:
Towards interval techniques for model validation. Computing 94(2-4): 257-269 (2012) - [j304]Nitaya Buntao, Vladik Kreinovich:
Uniqueness of reconstruction for Yager's t-norm combination of probabilistic and possibilistic knowledge. Int. J. Intell. Syst. 27(1): 16-22 (2012) - [j303]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20(1): 165-166 (2012) - [j302]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20(2): 315-316 (2012) - [j301]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20(3): 473-474 (2012) - [j300]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20(4): 629- (2012) - [j299]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20(5): 789- (2012) - [j298]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 20(6): 943- (2012) - [j297]Salamah Salamah, Ann Q. Gates, Vladik Kreinovich:
Validated templates for specification of complex LTL formulas. J. Syst. Softw. 85(8): 1915-1929 (2012) - [j296]Francisco Zapata, Vladik Kreinovich:
Reconstructing an Open Order from Its Closure, with Applications to Space-Time Physics and to Logic. Stud Logica 100(1-2): 419-435 (2012) - [j295]Jaime Nava, Vladik Kreinovich:
Towards Symmetry-Based Explanation of (Approximate) Shapes of Alpha-Helices and Beta-Sheets (and Beta-Barrels) in Protein Structure. Symmetry 4(1): 15-25 (2012) - [c88]Christopher Kiekintveld, Vladik Kreinovich:
Efficient Approximation for Security Games with Interval Uncertainty. AAAI Spring Symposium: Game Theory for Security, Sustainability, and Health 2012 - [c87]Vladik Kreinovich:
Towards Formalizing Non-monotonic Reasoning in Physics: Logical Approach Based on Physical Induction and Its Relation to Kolmogorov Complexity. Correct Reasoning 2012: 390-404 - [c86]Jaime Nava, Olga Kosheleva, Vladik Kreinovich:
Why bernstein polynomials are better: Fuzzy-inspired justification. FUZZ-IEEE 2012: 1-6 - [c85]Karen Villaverde, Nagwa Albehery, Tonghui Wang, Vladik Kreinovich:
Semi-heuristic poverty measures used by economists: Justification motivated by fuzzy techniques. FUZZ-IEEE 2012: 1-7 - [c84]Olga Kosheleva, Vladik Kreinovich:
How to divide students into groups so as to optimize learning: Towards a solution to a pedagogy-related optimization problem. SMC 2012: 1948-1953 - [p13]Olga Kosheleva, Vladik Kreinovich:
Can We Learn Algorithms from People Who Compute Fast: An Indirect Analysis in the Presence of Fuzzy Descriptions. Soft Computing in Humanities and Social Sciences 2012: 267-275 - 2011
- [j294]Irina Perfilieva
, Vladik Kreinovich:
Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling). Adv. Fuzzy Syst. 2011: 719256:1-719256:9 (2011) - [j293]Irina Perfilieva
, Vladik Kreinovich:
Why Fuzzy Transform Is Efficient in Large-Scale Prediction Problems: A Theoretical Explanation. Adv. Fuzzy Syst. 2011: 985839:1-985839:5 (2011) - [j292]Irina Perfilieva
, Vladik Kreinovich:
Fuzzy transform as a new paradigm in fuzzy modeling. Fuzzy Sets Syst. 180(1): 1-2 (2011) - [j291]Irina Perfilieva
, Vladik Kreinovich:
Fuzzy transforms of higher order approximate derivatives: A theorem. Fuzzy Sets Syst. 180(1): 55-68 (2011) - [j290]Luc Longpré, Christian Servin, Vladik Kreinovich:
Quantum computation techniques for gauging reliability of interval and fuzzy data. Int. J. Gen. Syst. 40(1): 99-109 (2011) - [j289]Vladik Kreinovich, Ladislav J. Kohout, Eunjin Kim:
Square root of 'not': a major difference between fuzzy and quantum logics. Int. J. Gen. Syst. 40(1): 111-127 (2011) - [j288]Vladik Kreinovich, Gang Xiang, Michael Oberguggenberger:
How to define a confidence set for functions: a new justification of the area method. Int. J. Gen. Syst. 40(7): 727-739 (2011) - [j287]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(1): 151-152 (2011) - [j286]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(2): 415-416 (2011) - [j285]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(3): 587-588 (2011) - [j284]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(4): 729-730 (2011) - [j283]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(5): 897-898 (2011) - [j282]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(6): 1059-1060 (2011) - [j281]Martine Ceberio, Vladik Kreinovich:
SCAN 2008 Guest editors preface. Reliab. Comput. 15(1) (2011) - [c83]Octavio Lerma, Vladik Kreinovich, Christopher Kiekintveld:
Linear-Time Resource Allocation in Security Games with Identical Fully Protective Resources. Applied Adversarial Reasoning and Risk Modeling 2011 - [c82]Vladik Kreinovich:
Cantor's Paradise Regained: Constructive Mathematics from Brouwer to Kolmogorov to Gelfond. Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning 2011: 181-190 - [c81]Steven Gutstein, Eric Freudenthal, Ali Jamal-Kamali, Vladik Kreinovich, David Morgenthaler:
Work in progress - The Rod-Spring approximation: An intuitive approach to the best-fit least-squares linear approximation. FIE 2011: S1 - [c80]Martine Ceberio, Vladik Kreinovich:
No-Free-Lunch Result for Interval and Fuzzy Computing: When Bounds Are Unusually Good, Their Computation Is Unusually Slow. MICAI (2) 2011: 13-23 - [c79]Vladik Kreinovich, Christelle Jacob, Didier Dubois, Janette Cardoso
, Martine Ceberio, Ildar Z. Batyrshin:
Estimating Probability of Failure of a Complex System Based on Inexact Information about Subsystems and Components, with Potential Applications to Aircraft Maintenance. MICAI (2) 2011: 70-81 - [c78]Vladik Kreinovich:
Towards Faster Estimation of Statistics and ODEs Under Interval, P-Box, and Fuzzy Uncertainty: From Interval Computations to Rough Set-Related Computations. RSFDGrC 2011: 3-10 - [c77]Jan Sliwka, Luc Jaulin, Martine Ceberio, Vladik Kreinovich:
Processing interval sensor data in the presence of outliers, with potential applications to localizing underwater robots. SMC 2011: 2330-2337 - [c76]Vladik Kreinovich:
From processing interval-valued fuzzy data to general type-2: Towards fast algorithms. T2FUZZ 2011 - [i1]Isaac E. Elishakoff, Vladik Kreinovich, Wolfram Luther, Evgenija D. Popova:
Uncertainty modeling and analysis with intervals: Foundations, tools, applications (Dagstuhl Seminar 11371). Dagstuhl Reports 1(9): 26-57 (2011) - 2010
- [j280]Vladik Kreinovich, Gang Xiang:
Estimating information amount under uncertainty: algorithmic solvability and computational complexity. Int. J. Gen. Syst. 39(4): 349-378 (2010) - [j279]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(1): 111-112 (2010) - [j278]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(2): 223-224 (2010) - [j277]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(3): 343-344 (2010) - [j276]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(4): 513-514 (2010) - [j275]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(5): 677-678 (2010) - [j274]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(6): 843-844 (2010) - [j273]Paulo Pinheiro da Silva, Aaron Velasco
, Olga Kosheleva, Vladik Kreinovich:
How AI-Type Uncertainty Ideas Can Improve Inter-Disciplinary Collaboration and Education: Lessons from a Case Study. J. Adv. Comput. Intell. Intell. Informatics 14(6): 700-707 (2010) - [j272]Guoqing Liu, Vladik Kreinovich:
Fast convolution and Fast Fourier Transform under interval and fuzzy uncertainty. J. Comput. Syst. Sci. 76(1): 63-76 (2010) - [j271]Vladik Kreinovich, Bartlomiej Jacek Kubica:
From Computing Sets of Optima, Pareto Sets, and Sets of Nash Equilibria to General Decision-Related Set Computations. J. Univers. Comput. Sci. 16(18): 2657-2685 (2010) - [c75]Vladik Kreinovich:
Metrization Theorem for Space-Times: From Urysohn's Problem towards Physically Useful Constructive Mathematics. Fields of Logic and Computation 2010: 470-487 - [c74]Aline Jaimes, Craig E. Tweedie, Tanja Magoc, Vladik Kreinovich, Martine Ceberio:
Multi-objective optimization under positivity constraints, with a meteorological example. FUZZ-IEEE 2010: 1-7 - [c73]Vladik Kreinovich, Olga Kosheleva:
Towards a more natural proof of metrization theorem for space-times. FUZZ-IEEE 2010: 1-8 - [c72]Gang Xiang, Vladik Kreinovich:
Towards improved trapezoidal approximation to intersection (fusion) of trapezoidal fuzzy numbers: Specific procedure and general non-associativity theorem. FUZZ-IEEE 2010: 1-6 - [c71]Vladik Kreinovich, Jaime Nava, Rodrigo A. Romero, Julio C. Olaya, Aaron Velasco
, Kate C. Miller:
Spatial Resolution for Processing Seismic Data: Type-2 Methods for Finding the Relevant Granular Structure. GrC 2010: 259-264 - [c70]Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta:
Symmetries: A General Approach to Integrated Uncertainty Management. IUM 2010: 141-152
2000 – 2009
- 2009
- [j270]Vladik Kreinovich:
Toward Formalizing Non-Monotonic Reasoning in Physics: the Use of Kolmogorov Complexity. Inteligencia Artif. 13(41): 4-20 (2009) - [j269]