| 2013 | ||
|---|---|---|
| j32 | Peerapon Vateekul, Sareewan Dendamrongvit, Miroslav Kubat: Improving SVM Performance in Multi-Label Domains: Threshold Adjustment. International Journal on Artificial Intelligence Tools 22(1) (2013) | |
| 2011 | ||
| j31 | Sareewan Dendamrongvit, Peerapon Vateekul, Miroslav Kubat: Irrelevant attributes and imbalanced classes in multi-label text-categorization domains. Intell. Data Anal. 15(6): 843-859 (2011) | |
| j30 | Thanuka Wickramarathne, Kamal Premaratne, Miroslav Kubat, D. T. Jayaweera: CoFiDS: A Belief-Theoretic Approach for Automated Collaborative Filtering. IEEE Trans. Knowl. Data Eng. 23(2): 175-189 (2011) | |
| 2010 | ||
| j29 | Thiago Quirino, Miroslav Kubat, Nicholas J. Bryan: Instinct-Based Mating in Genetic Algorithms Applied to the Tuning of 1-NN Classifiers. IEEE Trans. Knowl. Data Eng. 22(12): 1724-1737 (2010) | |
| p2 | Miroslav Kubat, Kanoksri Sarinnapakorn, Sareewan Dendamrongvit: Induction in Multi-Label Text Classification Domains. Advances in Machine Learning II 2010: 225-244 | |
| 2009 | ||
| j28 | Kasun Wickramaratna, Miroslav Kubat, Kamal Premaratne: Predicting Missing Items in Shopping Carts. IEEE Trans. Knowl. Data Eng. 21(7): 985-998 (2009) | |
| c27 | Kasun Wickramaratna, Miroslav Kubat, Kamal Premaratne, Thanuka Wickramarathne: Rule Mining and Missing-Value Prediction in the Presence of Data Ambiguities. FLAIRS Conference 2009 | |
| c26 | Peerapon Vateekul, Miroslav Kubat: Fast Induction of Multiple Decision Trees in Text Categorization from Large Scale, Imbalanced, and Multi-label Data. ICDM Workshops 2009: 320-325 | |
| c25 | Sareewan Dendamrongvit, Miroslav Kubat: Undersampling Approach for Imbalanced Training Sets and Induction from Multi-label Text-Categorization Domains. PAKDD Workshops 2009: 40-52 | |
| 2008 | ||
| j27 | Kanoksri Sarinnapakorn, Miroslav Kubat: Induction from Multi-Label Examples in Information Retrieval Systems: a Case Study. Applied Artificial Intelligence 22(5): 407-432 (2008) | |
| j26 | Kasun Wickramaratna, Miroslav Kubat, Peter J. Minnett: Discovering numeric laws, a case study: CO_2 fugacity in the ocean. Intell. Data Anal. 12(4): 379-391 (2008) | |
| j25 | Hans Holland, Miroslav Kubat, Jan Zizka: Handling Ambiguous Values in Instance-Based Classifiers. International Journal on Artificial Intelligence Tools 17(3): 449-463 (2008) | |
| p1 | S. P. Subasingha, J. Zhang, Kamal Premaratne, Mei-Ling Shyu, Miroslav Kubat, K. K. Rohitha Hewawasam: Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method. Data Mining: Foundations and Practice 2008: 539-562 | |
| 2007 | ||
| j24 | Wadee S. Alhalabi, Miroslav Kubat, Moiez A. Tapia: A Tool to Personalize the Ranking of the Documents Returned by an Internet Search Engine. JCIT 2(3): 6-10 (2007) | |
| j23 | Wadee S. Alhalabi, Miroslav Kubat, Moiez A. Tapia: Search engine ranking efficiency evaluation tool. SIGCSE Bulletin 39(2): 97-101 (2007) | |
| j22 | Kanoksri Sarinnapakorn, Miroslav Kubat: Combining Subclassifiers in Text Categorization: A DST-Based Solution and a Case Study. IEEE Trans. Knowl. Data Eng. 19(12): 1638-1651 (2007) | |
| c24 | Hans Holland, Miroslav Kubat, Jan Zizka: Instance-Based Classifiers Dealing with Ambiguous Attributes and Class Labels. FLAIRS Conference 2007: 598-603 | |
| c23 | Kasun Wickramaratna, Miroslav Kubat, Peter J. Minnett: Automated Search for the Quantitative Laws Affecting CO2 Fugacity in Sea Water. FLAIRS Conference 2007: 638-640 | |
| c22 | Kanoksri Sarinnapakorn, Miroslav Kubat: Induction from Multi-Label Training Examples in Text Categorization: Combining Subclassifiers (a Case Study). IC-AI 2007: 351-357 | |
| 2006 | ||
| j21 | Yu Li, Miroslav Kubat: Searching for high-support itemsets in itemset trees. Intell. Data Anal. 10(2): 105-120 (2006) | |
| 2005 | ||
| j20 | Antonin Rozsypal, Miroslav Kubat: Association mining in time-varying domains. Intell. Data Anal. 9(3): 273-288 (2005) | |
| c21 | Xiaoyuan Su, Miroslav Kubat, Moiez A. Tapia, Chao Hu: Query Size Estimation Using Clustering Techniques. ICTAI 2005: 185-189 | |
| 2004 | ||
| j19 | Miroslav Kubat, Joao Gama, Paul E. Utgoff: Incremental learning and concept drift: Editor's introduction. Intell. Data Anal. 8(3): 211-212 (2004) | |
| c20 | Miroslav Kubat: Induction in Time-Varying Domains: Motivation, Origins, and Encouragements. ECBS 2004: 316-322 | |
| 2003 | ||
| j18 | Antonin Rozsypal, Miroslav Kubat: Selecting representative examples and attributes by a genetic algorithm. Intell. Data Anal. 7(4): 291-304 (2003) | |
| j17 | Miroslav Kubat, Aladdin Hafez, Vijay V. Raghavan, Jayakrishna R. Lekkala, Wei Kian Chen: Itemset Trees for Targeted Association Querying. IEEE Trans. Knowl. Data Eng. 15(6): 1522-1534 (2003) | |
| c19 | Antonin Rozsypal, Miroslav Kubat: Association Mining in Gradually Changing Domains. FLAIRS Conference 2003: 366-370 | |
| 2002 | ||
| c18 | Ronnie Fanguy, Miroslav Kubat: Modifying Upstart for Use in Multiclass Numerical Domains. FLAIRS Conference 2002: 339-343 | |
| 2001 | ||
| j16 | Yves Lespérance, Gerd Wagner, William P. Birmingham, Kurt D. Bollacker, Alexander Nareyek, J. Paul Walser, David W. Aha, Timothy W. Finin, Benjamin N. Grosof, Nathalie Japkowicz, Robert Holte, Lise Getoor, Carla P. Gomes, Holger H. Hoos, Alan C. Schultz, Miroslav Kubat, Tom M. Mitchell, Jörg Denzinger, Yolanda Gil, Karen L. Myers, Claudio Bettini, Angelo Montanari: AAAI 2000 Workshop Reports. AI Magazine 22(1): 127-136 (2001) | |
| j15 | Miroslav Kubat, Martin Cooperson Jr.: A reduction technique for nearest-neighbor classification: Small groups of examples. Intell. Data Anal. 5(6): 463-476 (2001) | |
| c17 | Antonin Rozsypal, Miroslav Kubat: Using the Genetic Algorithm to Reduce the Size of a Nearest-Neighbor Classifier and to Select Relevant Attributes. ICML 2001: 449-456 | |
| 2000 | ||
| j14 | ||
| c16 | ||
| c15 | Miroslav Kubat, Jan Zizka: Learning Middle Game Patterns in Chess: A Case Study. IEA/AIE 2000: 426-432 | |
| c14 | Ryan G. Benton, Miroslav Kubat, Rasiah Loganantharaj: Meta-classifiers and Selective Superiority. IEA/AIE 2000: 434-442 | |
| 1999 | ||
| c13 | Miroslav Kubat, Martin Cooperson Jr.: Initializing RBF-Networks with Small Subsets of Training Examples. AAAI/IAAI 1999: 188-193 | |
| 1998 | ||
| j13 | Miroslav Kubat, Robert C. Holte, Stan Matwin: Machine Learning for the Detection of Oil Spills in Satellite Radar Images. Machine Learning 30(2-3): 195-215 (1998) | |
| j12 | ||
| 1997 | ||
| c12 | Miroslav Kubat, Robert C. Holte, Stan Matwin: Learning When Negative Examples Abound. ECML 1997: 146-153 | |
| c11 | Miroslav Kubat, Stan Matwin: Addressing the Curse of Imbalanced Training Sets: One-Sided Selection. ICML 1997: 179-186 | |
| 1996 | ||
| j11 | Gerhard Widmer, Miroslav Kubat: Learning in the Presence of Concept Drift and Hidden Contexts. Machine Learning 23(1): 69-101 (1996) | |
| c10 | ||
| 1995 | ||
| j10 | Simon Parsons, Miroslav Kubat, Mirko Dohnal: A rough set approach to reasoning under uncertainty. J. Exp. Theor. Artif. Intell. 7(2): 175-193 (1995) | |
| j9 | Irena Ivanova, Miroslav Kubat: Initialization of neural networks by means of decision trees. Knowl.-Based Syst. 8(6): 333-344 (1995) | |
| c9 | Miroslav Kubat, Doris Flotzinger: Pruning Multivariate Decision Trees by Hyperplane Merging. ECML 1995: 190-199 | |
| c8 | Irena Ivanova, Miroslav Kubat: Decision-Tree Based Neural Network (Extended Abstract). ECML 1995: 295-298 | |
| c7 | Miroslav Kubat, Gerhard Widmer: Adapting to Drift in Continuous Domains (Extended Abstract). ECML 1995: 307-310 | |
| c6 | ||
| 1994 | ||
| j8 | Libor Spacek, Miroslav Kubat, Doris Flotzinger: Face recognition through learning boundary characteristics. Applied Artificial Intelligence 8(1): 149-164 (1994) | |
| j7 | Miroslav Kubat, Gert Pfurtscheller, Doris Flotzinger: AI-based approach to automatic sleep classification. Biological Cybernetics 70(5): 443-448 (1994) | |
| j6 | Miroslav Kubat, Simon Parsons: Approximating Knowledge in a Multi-Agent System. Informatica (Slovenia) 18(2) (1994) | |
| 1993 | ||
| j5 | Miroslav Kubat: Flexible concept learning in real-time systems. Journal of Intelligent and Robotic Systems 8(2): 155-171 (1993) | |
| c5 | Gerhard Widmer, Miroslav Kubat: Effective Learning in Dynamic Environments by Explicit Context Tracking. ECML 1993: 227-243 | |
| c4 | Miroslav Kubat, Doris Flotzinger, Gert Pfurtscheller: Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods. ECML 1993: 366-371 | |
| 1992 | ||
| j4 | Miroslav Kubat, Ivana Krizakova: Forgetting and aging of knowledge in concept formation. Applied Artificial Intelligence 6(2): 195-206 (1992) | |
| j3 | Miroslav Kubat: Conceptual Inductive Learning: The Case of Unreliable Teachers. Artif. Intell. 52(2): 169-182 (1992) | |
| j2 | Ivana Krizakova, Miroslav Kubat: FAVORIT: Concept formation with ageing of knowledge. Pattern Recognition Letters 13(1): 19-25 (1992) | |
| c3 | Miroslav Kubat: Introduction to Machine Learning. Advanced Topics in Artificial Intelligence 1992: 104-138 | |
| c2 | Gerhard Widmer, Miroslav Kubat: Learning Flexible Concepts from Streams of Examples: FLORA 2. ECAI 1992: 463-467 | |
| 1991 | ||
| c1 | Miroslav Kubat, Jirina Pavlickova: The System FLORA: Learning from Type-Varying Training Sets. EWSL 1991: 234 | |
| 1989 | ||
| j1 | Miroslav Kubat: Floating approximation in time-varying knowledge bases. Pattern Recognition Letters 10(4): 223-227 (1989) | |
Colors in the list of coauthors
Last update Wed May 22 21:53:11 2013 CET by the DBLP Team —
Data released under the ODC-BY 1.0 license — See also our legal information page