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Miroslav Kubat: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Miroslav Kubat, Martin Cooperson Jr.
    Initializing RBF-Networks with Small Subsets of Training Examples. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1999, pp:188-193 [Conf]
  2. Miroslav Kubat
    Introduction to Machine Learning. [Citation Graph (0, 0)][DBLP]
    Advanced Topics in Artificial Intelligence, 1992, pp:104-138 [Conf]
  3. Gerhard Widmer, Miroslav Kubat
    Learning Flexible Concepts from Streams of Examples: FLORA 2. [Citation Graph (0, 0)][DBLP]
    ECAI, 1992, pp:463-467 [Conf]
  4. Miroslav Kubat
    Induction in Time-Varying Domains: Motivation, Origins, and Encouragements. [Citation Graph (0, 0)][DBLP]
    ECBS, 2004, pp:316-322 [Conf]
  5. Irena Ivanova, Miroslav Kubat
    Decision-Tree Based Neural Network (Extended Abstract). [Citation Graph (0, 0)][DBLP]
    ECML, 1995, pp:295-298 [Conf]
  6. Miroslav Kubat, Doris Flotzinger
    Pruning Multivariate Decision Trees by Hyperplane Merging. [Citation Graph (0, 0)][DBLP]
    ECML, 1995, pp:190-199 [Conf]
  7. Miroslav Kubat, Doris Flotzinger, Gert Pfurtscheller
    Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods. [Citation Graph (0, 0)][DBLP]
    ECML, 1993, pp:366-371 [Conf]
  8. Miroslav Kubat, Robert C. Holte, Stan Matwin
    Learning When Negative Examples Abound. [Citation Graph (0, 0)][DBLP]
    ECML, 1997, pp:146-153 [Conf]
  9. Miroslav Kubat, Jirina Pavlickova
    The System FLORA: Learning from Type-Varying Training Sets. [Citation Graph (0, 0)][DBLP]
    EWSL, 1991, pp:234- [Conf]
  10. Miroslav Kubat, Gerhard Widmer
    Adapting to Drift in Continuous Domains (Extended Abstract). [Citation Graph (0, 0)][DBLP]
    ECML, 1995, pp:307-310 [Conf]
  11. Gerhard Widmer, Miroslav Kubat
    Effective Learning in Dynamic Environments by Explicit Context Tracking. [Citation Graph (0, 0)][DBLP]
    ECML, 1993, pp:227-243 [Conf]
  12. Ronnie Fanguy, Miroslav Kubat
    Modifying Upstart for Use in Multiclass Numerical Domains. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2002, pp:339-343 [Conf]
  13. Antonin Rozsypal, Miroslav Kubat
    Association Mining in Gradually Changing Domains. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2003, pp:366-370 [Conf]
  14. Miroslav Kubat
    Second Tier for Decision Trees. [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:293-301 [Conf]
  15. Miroslav Kubat, Martin Cooperson Jr.
    Voting Nearest-Neighbor Subclassifiers. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:503-510 [Conf]
  16. Miroslav Kubat, Stan Matwin
    Addressing the Curse of Imbalanced Training Sets: One-Sided Selection. [Citation Graph (0, 0)][DBLP]
    ICML, 1997, pp:179-186 [Conf]
  17. Antonin Rozsypal, Miroslav Kubat
    Using the Genetic Algorithm to Reduce the Size of a Nearest-Neighbor Classifier and to Select Relevant Attributes. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:449-456 [Conf]
  18. Xiaoyuan Su, Miroslav Kubat, Moiez A. Tapia, Chao Hu
    Query Size Estimation Using Clustering Techniques. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2005, pp:185-189 [Conf]
  19. Ryan Benton, Miroslav Kubat, Rasiah Loganantharaj
    Meta-classifiers and Selective Superiority. [Citation Graph (0, 0)][DBLP]
    IEA/AIE, 2000, pp:434-442 [Conf]
  20. Miroslav Kubat, Jan Zizka
    Learning Middle Game Patterns in Chess: A Case Study. [Citation Graph (0, 0)][DBLP]
    IEA/AIE, 2000, pp:426-432 [Conf]
  21. Miroslav Kubat, Ivana Krizakova
    Forgetting and aging of knowledge in concept formation. [Citation Graph (0, 0)][DBLP]
    Applied Artificial Intelligence, 1992, v:6, n:2, pp:195-206 [Journal]
  22. Libor Spacek, Miroslav Kubat, Doris Flotzinger
    Face recognition through learning boundary characteristics. [Citation Graph (0, 0)][DBLP]
    Applied Artificial Intelligence, 1994, v:8, n:1, pp:149-164 [Journal]
  23. Miroslav Kubat
    Conceptual Inductive Learning: The Case of Unreliable Teachers. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1992, v:52, n:2, pp:169-182 [Journal]
  24. 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. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2001, v:22, n:1, pp:127-136 [Journal]
  25. Yu Li, Miroslav Kubat
    Searching for high-support itemsets in itemset trees. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2006, v:10, n:2, pp:105-120 [Journal]
  26. Miroslav Kubat, Martin Cooperson Jr.
    A reduction technique for nearest-neighbor classification: Small groups of examples. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2001, v:5, n:6, pp:463-476 [Journal]
  27. Miroslav Kubat, Joao Gama, Paul E. Utgoff
    Incremental learning and concept drift: Editor's introduction. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2004, v:8, n:3, pp:211-212 [Journal]
  28. Antonin Rozsypal, Miroslav Kubat
    Association mining in time-varying domains. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2005, v:9, n:3, pp:273-288 [Journal]
  29. Antonin Rozsypal, Miroslav Kubat
    Selecting representative examples and attributes by a genetic algorithm. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2003, v:7, n:4, pp:291-304 [Journal]
  30. Miroslav Kubat
    Recycling Decision Trees in Numeric Domains. [Citation Graph (0, 0)][DBLP]
    Informatica (Slovenia), 2000, v:24, n:2, pp:- [Journal]
  31. Miroslav Kubat, Simon Parsons
    Approximating Knowledge in a Multi-Agent System. [Citation Graph (0, 0)][DBLP]
    Informatica (Slovenia), 1994, v:18, n:2, pp:- [Journal]
  32. Irena Ivanova, Miroslav Kubat
    Initialization of neural networks by means of decision trees. [Citation Graph (0, 0)][DBLP]
    Knowl.-Based Syst., 1995, v:8, n:6, pp:333-344 [Journal]
  33. Miroslav Kubat, Robert C. Holte, Stan Matwin
    Machine Learning for the Detection of Oil Spills in Satellite Radar Images. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:30, n:2-3, pp:195-215 [Journal]
  34. Gerhard Widmer, Miroslav Kubat
    Learning in the Presence of Concept Drift and Hidden Contexts. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1996, v:23, n:1, pp:69-101 [Journal]
  35. Gerhard Widmer, Miroslav Kubat
    Guest Editors' Introduction. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:32, n:2, pp:83-84 [Journal]
  36. Ivana Krizakova, Miroslav Kubat
    FAVORIT: Concept formation with ageing of knowledge. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1992, v:13, n:1, pp:19-25 [Journal]
  37. Miroslav Kubat
    Floating approximation in time-varying knowledge bases. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1989, v:10, n:4, pp:223-227 [Journal]
  38. Miroslav Kubat, Aladdin Hafez, Vijay V. Raghavan, Jayakrishna R. Lekkala, Wei Kian Chen
    Itemset Trees for Targeted Association Querying. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Knowl. Data Eng., 2003, v:15, n:6, pp:1522-1534 [Journal]
  39. Kasun Wickramaratna, Miroslav Kubat, Peter Minnett
    Automated Search for the Quantitative Laws Affecting CO2 Fugacity in Sea Water. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2007, pp:638-0 [Conf]
  40. Hans Holland, Miroslav Kubat, Jan Zizka
    Instance-Based Classifiers Dealing with Ambiguous Attributes and Class Labels. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2007, pp:598-603 [Conf]
  41. Kanoksri Sarinnapakorn, Miroslav Kubat
    Combining Subclassifiers in Text Categorization: A DST-Based Solution and a Case Study. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Knowl. Data Eng., 2007, v:19, n:12, pp:1638-1651 [Journal]

  42. Rule Mining and Missing-Value Prediction in the Presence of Data Ambiguities. [Citation Graph (, )][DBLP]


  43. Induction from Multi-Label Training Examples in Text Categorization: Combining Subclassifiers (a Case Study). [Citation Graph (, )][DBLP]


  44. Fast Induction of Multiple Decision Trees in Text Categorization from Large Scale, Imbalanced, and Multi-label Data. [Citation Graph (, )][DBLP]


  45. Undersampling Approach for Imbalanced Training Sets and Induction from Multi-label Text-Categorization Domains. [Citation Graph (, )][DBLP]


  46. Induction from Multi-Label Examples in Information Retrieval Systems: a Case Study. [Citation Graph (, )][DBLP]


  47. AI-based approach to automatic sleep classification. [Citation Graph (, )][DBLP]


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