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ORCIDTheodore B. Trafalis
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2020 – today
- 2024
[j44]Elaheh Jafarigol, Theodore B. Trafalis:
A distributed approach to meteorological predictions: addressing data imbalance in precipitation prediction models through federated learning and GANs. Comput. Manag. Sci. 21(1): 22 (2024)- 2023
- [c18]Wei Sun, Theodore B. Trafalis:
Learning-Based Nonlinear H∞ Control via Game-Theoretic Differential Dynamic Programming. ACC 2023: 1283-1288 - [i6]Elaheh Jafarigol, Theodore B. Trafalis:
A Review of Machine Learning Techniques in Imbalanced Data and Future Trends. CoRR abs/2310.07917 (2023) - [i5]Elaheh Jafarigol, William Keely, Tess Hartog, Tom Welborn, Peyman Hekmatpour, Theodore B. Trafalis:
Religious Affiliation in the Twenty-First Century: A Machine Learning Perspective on the World Value Survey. CoRR abs/2310.10874 (2023) - [i4]Elaheh Jafarigol, Theodore B. Trafalis:
A Distributed Approach to Meteorological Predictions: Addressing Data Imbalance in Precipitation Prediction Models through Federated Learning and GANs. CoRR abs/2310.13161 (2023) - [i3]Elaheh Jafarigol, Theodore B. Trafalis:
The Paradox of Noise: An Empirical Study of Noise-Infusion Mechanisms to Improve Generalization, Stability, and Privacy in Federated Learning. CoRR abs/2311.05790 (2023) - [i2]Elaheh Jafarigol, Theodore B. Trafalis, Talayeh Razzaghi, Mona Zamankhani:
Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations. CoRR abs/2311.10832 (2023) - 2022
- [j43]Ismail I. Almaraj
, Theodore B. Trafalis:
A robust optimization approach in a multi-objective closed-loop supply chain model under imperfect quality production. Ann. Oper. Res. 319(2): 1479-1505 (2022) - [j42]Mahmud R. Siamizade, Theodore B. Trafalis:
A robust global optimisation framework for stochastic integrated refinery planning with demand and price uncertainties. Int. J. Math. Oper. Res. 22(4): 496-527 (2022) - [c17]Xiaomeng Dong, Tao Tan, Michael Potter, Yun-Chan Tsai, Gaurav Kumar, V. Ratna Saripalli, Theodore B. Trafalis:
Autonomous Learning Rate Optimization for Deep Learning. LION 2022: 292-305 - [c16]Xiaomeng Dong, Michael Potter, Gaurav Kumar, Yun-Chan Tsai, V. Ratna Saripalli, Theodore B. Trafalis:
Optimizing Data Augmentation Policy Through Random Unidimensional Search. LION 2022: 306-318 - 2021
- [c15]Dimitrios I. Diochnos, Theodore B. Trafalis:
Learning Reliable Rules under Class Imbalance. SDM 2021: 28-36 - [i1]Wei Sun, Theodore B. Trafalis:
Learning-Based Nonlinear H∞ Control via Game-Theoretic Differential Dynamic Programming. CoRR abs/2107.04507 (2021) - 2020
- [j41]Alexander M. Malyscheff, Theodore B. Trafalis:
Kernel classification using a linear programming approach. Ann. Math. Artif. Intell. 88(1-3): 39-51 (2020) - [j40]Ismail I. Almaraj, Theodore B. Trafalis:
Affinely adjustable robust optimization under dynamic uncertainty set for a novel robust closed-loop supply chain. Comput. Ind. Eng. 145: 106521 (2020) - [j39]Hamoud S. Bin Obaid, Theodore B. Trafalis:
An approximation to max min fairness in multi commodity networks. Comput. Manag. Sci. 17(1): 65-77 (2020) - [j38]Fuad Aleskerov, Sergey Demin, Michael B. Richman, Sergey Shvydun, Theodore B. Trafalis, Vyacheslav Yakuba:
Constructing an Efficient Machine Learning Model for Tornado Prediction. Int. J. Inf. Technol. Decis. Mak. 19(5): 1177-1187 (2020) - [j37]Elaheh Jafarigol, Theodore B. Trafalis:
Imbalanced Learning with Parametric Linear Programming Support Vector Machine for Weather Data Application. SN Comput. Sci. 1(6): 360 (2020) - [j36]Md. Manjurul Ahsan, Tasfiq E. Alam, Theodore B. Trafalis, Pedro Huebner:
Deep MLP-CNN Model Using Mixed-Data to Distinguish between COVID-19 and Non-COVID-19 Patients. Symmetry 12(9): 1526 (2020)
2010 – 2019
- 2018
- [j35]Maher Maalouf, Dirar Homouz, Theodore B. Trafalis:
Logistic regression in large rare events and imbalanced data: A performance comparison of prior correction and weighting methods. Comput. Intell. 34(1): 161-174 (2018) - 2017
- [j34]Emre Tokgöz, Theodore B. Trafalis:
2-Facility manifold location routing problem. Optim. Lett. 11(2): 389-405 (2017) - [j33]Robin C. Gilbert, Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie:
A data-driven kernel method assimilation technique for geophysical modelling. Optim. Methods Softw. 32(2): 237-249 (2017) - [c14]XueYan Mei, Xiaomeng Dong, Timothy Deyer, Jingyi Zeng, Theodore B. Trafalis, Yan Fang:
Thyroid Nodule Benignty Prediction by Deep Feature Extraction. BIBE 2017: 241-245 - 2015
- [j32]Emre Tokgöz, Samir A. Alwazzi, Theodore B. Trafalis:
A heuristic algorithm to solve the single-facility location routing problem on Riemannian surfaces. Comput. Manag. Sci. 12(3): 397-415 (2015) - [c13]Emre Tokgöz, Iddrisu Awudu, Theodore B. Trafalis:
A Single-Facility Manifold Location Routing Problem with an Application to Supply Chain Management and Robotics. MOD 2015: 130-144 - [e1]Asim Roy, Plamen Angelov, Adel M. Alimi, Ganesh Kumar Venayagamoorthy, Theodore B. Trafalis:
INNS Conference on Big Data 2015, San Francisco, CA, USA, 8-10 August 2015. Procedia Computer Science 53, Elsevier 2015 [contents] - 2014
- [j31]Victoria C. P. Chen, Seoung Bum Kim, Theodore B. Trafalis:
Preface: Special volume on data mining and informatics. Ann. Oper. Res. 216(1): 1-2 (2014) - [j30]Theodore B. Trafalis, Indra Adrianto, Michael B. Richman, S. Lakshmivarahan:
Machine-learning classifiers for imbalanced tornado data. Comput. Manag. Sci. 11(4): 403-418 (2014) - [j29]Cameron A. MacKenzie, Theodore B. Trafalis, Kash Barker:
A Bayesian beta kernel model for binary classification and online learning problems. Stat. Anal. Data Min. 7(6): 434-449 (2014) - 2013
- [j28]Nicolas P. Couellan, Theodore B. Trafalis:
An incremental primal-dual method for nonlinear programming with special structure. Optim. Lett. 7(1): 51-62 (2013) - [j27]Nicolas P. Couellan, Theodore B. Trafalis:
On-line SVM learning via an incremental primal-dual technique. Optim. Methods Softw. 28(2): 256-275 (2013) - [c12]Zhen Zhang, Theodore B. Trafalis:
Time-series Analysis for Detecting Structure Changes and Suspicious Accounting Activities in Public Software Companies. Complex Adaptive Systems 2013: 466-471 - 2011
- [j26]Theodore B. Trafalis, Olutayo O. Oladunni, Michael B. Richman:
Linear classification tikhonov regularization knowledge-based support vector machine for tornado forecasting. Comput. Manag. Sci. 8(3): 281-297 (2011) - [j25]Maher Maalouf, Theodore B. Trafalis, Indra Adrianto:
Kernel logistic regression using truncated Newton method. Comput. Manag. Sci. 8(4): 415-428 (2011) - [j24]Maher Maalouf, Theodore B. Trafalis:
Robust weighted kernel logistic regression in imbalanced and rare events data. Comput. Stat. Data Anal. 55(1): 168-183 (2011) - [j23]Maher Maalouf, Theodore B. Trafalis:
Rare events and imbalanced datasets: an overview. Int. J. Data Min. Model. Manag. 3(4): 375-388 (2011) - [j22]Olutayo O. Oladunni, Theodore B. Trafalis:
Single-phase fluid flow classification via learning models. Int. J. Gen. Syst. 40(05): 561-576 (2011) - 2010
- [j21]Theodore B. Trafalis, Samir A. Alwazzi:
Support vector machine classification with noisy data: a second order cone programming approach. Int. J. Gen. Syst. 39(7): 757-781 (2010) - [j20]Indra Adrianto, Theodore B. Trafalis:
The p-Centre machine for regression analysis. Optim. Methods Softw. 25(2): 171-183 (2010)
2000 – 2009
- 2009
- [j19]O. Erhun Kundakcioglu, Marcello Sanguineti, Theodore B. Trafalis:
Guest Editorial. Comput. Manag. Sci. 6(1): 1-3 (2009) - [j18]Olutayo O. Oladunni, Theodore B. Trafalis:
A nonlinear multi-classification knowledge-based kernel machine. Comput. Manag. Sci. 6(1): 81-100 (2009) - [j17]Olutayo O. Oladunni, Theodore B. Trafalis:
A regularized pairwise multi-classification knowledge-based machine and applications. Eur. J. Oper. Res. 195(3): 924-941 (2009) - [j16]Indra Adrianto, Theodore B. Trafalis, Valliappa Lakshmanan:
Support vector machines for spatiotemporal tornado prediction. Int. J. Gen. Syst. 38(7): 759-776 (2009) - [j15]Robin C. Gilbert, Theodore B. Trafalis:
Quadratic programming formulations for classificationand regression. Optim. Methods Softw. 24(2): 175-185 (2009) - [r1]Theodore B. Trafalis, Suat Kasap:
Neural Networks for Combinatorial Optimization. Encyclopedia of Optimization 2009: 2547-2555 - 2008
- [j14]Abdulrahman Alenezi, Scott A. Moses, Theodore B. Trafalis:
Real-time prediction of order flowtimes using support vector regression. Comput. Oper. Res. 35(11): 3489-3503 (2008) - [j13]Huseyin Ince, Theodore B. Trafalis:
Short term forecasting with support vector machines and application to stock price prediction. Int. J. Gen. Syst. 37(6): 677-687 (2008) - 2007
- [j12]Budi Santosa, Theodore B. Trafalis:
Robust multiclass kernel-based classifiers. Comput. Optim. Appl. 38(2): 261-279 (2007) - [j11]Theodore B. Trafalis, Samir A. Alwazzi:
Support vector regression with noisy data: a second order cone programming approach. Int. J. Gen. Syst. 36(2): 237-250 (2007) - [j10]Theodore B. Trafalis, Robin C. Gilbert:
Robust support vector machines for classification and computational issues. Optim. Methods Softw. 22(1): 187-198 (2007) - [c11]Olutayo O. Oladunni, Theodore B. Trafalis:
Regularized Knowledge-Based Kernel Machine. International Conference on Computational Science (1) 2007: 176-183 - [c10]Theodore B. Trafalis, Indra Adrianto, Michael B. Richman:
Active Learning with Support Vector Machines for Tornado Prediction. International Conference on Computational Science (1) 2007: 1130-1137 - [c9]Olutayo O. Oladunni, Theodore B. Trafalis:
Regularization Based Classification Models. IJCNN 2007: 25-30 - 2006
- [j9]Theodore B. Trafalis:
Foreword. Comput. Manag. Sci. 3(2): 101-102 (2006) - [j8]Huseyin Ince, Theodore B. Trafalis:
A hybrid model for exchange rate prediction. Decis. Support Syst. 42(2): 1054-1062 (2006) - [j7]Theodore B. Trafalis, Robin C. Gilbert:
Robust classification and regression using support vector machines. Eur. J. Oper. Res. 173(3): 893-909 (2006) - [j6]Huseyin Ince, Theodore B. Trafalis:
Kernel methods for short-term portfolio management. Expert Syst. Appl. 30(3): 535-542 (2006) - [j5]Theodore B. Trafalis, Budi Santosa, Michael B. Richman:
Learning networks for tornado detection. Int. J. Gen. Syst. 35(1): 93-107 (2006) - [c8]Olutayo O. Oladunni, Theodore B. Trafalis, Dimitrios V. Papavassiliou:
Knowledge-Based Multiclass Support Vector Machines Applied to Vertical Two-Phase Flow. International Conference on Computational Science (1) 2006: 188-195 - [c7]Hyung-Jin Son, Theodore B. Trafalis:
Detection of Tornados Using an Incremental Revised Support Vector Machine with Filters. International Conference on Computational Science (3) 2006: 506-513 - [c6]Olutayo O. Oladunni, Theodore B. Trafalis:
A Pairwise Reduced Kernel-based Multi-classification Tikhonov Regularization Machine. IJCNN 2006: 130-137 - 2005
- [j4]Theodore B. Trafalis, Budi Santosa, Michael B. Richman:
Learning networks in rainfall estimation. Comput. Manag. Sci. 2(3): 229-251 (2005) - 2004
- [c5]Theodore B. Trafalis, Budi Santosa, Michael B. Richman:
Rule-Based Support Vector Machine Classifiers Applied to Tornado Prediction. International Conference on Computational Science 2004: 678-684 - 2003
- [c4]Theodore B. Trafalis, Huseyin Ince, Michael B. Richman:
Tornado Detection with Support Vector Machines. International Conference on Computational Science 2003: 289-298 - 2002
- [j3]Theodore B. Trafalis, Suat Kasap:
A novel metaheuristics approach for continuous global optimization. J. Glob. Optim. 23(2): 171-190 (2002) - [j2]Theodore B. Trafalis, Alexander M. Malyscheff:
An Analytic Center Machine. Mach. Learn. 46(1-3): 203-223 (2002) - 2000
- [c3]Theodore B. Trafalis, Huseyin Ince:
Support Vector Machine for Regression and Applications to Financial Forecasting. IJCNN (6) 2000: 348-353
1990 – 1999
- 1999
- [p1]Theodore B. Trafalis, Suat Kasap:
Neural Networks Approaches for Combinatorial Optimization Problems. Handbook of Combinatorial Optimization 1999: 259-293 - 1997
- [c2]Theodore B. Trafalis, Nicolas P. Couellan, Sébastien C. Bertrand:
Training of supervised neural networks via a nonlinear primal-dual interior-point method. ICNN 1997: 2017-2021 - 1996
- [j1]Theodore B. Trafalis, Nicolas P. Couellan:
Neural network training via an affine scaling quadratic optimization algorithm. Neural Networks 9(3): 475-481 (1996) - 1990
- [c1]Mark J. Kaiser, Thomas L. Morin, Theodore B. Trafalis:
Centers and Invariant Points of Convex Bodies. Applied Geometry And Discrete Mathematics 1990: 367-386
Coauthor Index
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