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Pavel Brazdil
2010 – today
- 2013
[c40]- 2012
- [c39]Rui Leite, Pavel Brazdil, Joaquin Vanschoren: Selecting Classification Algorithms with Active Testing. MLDM 2012: 117-131
- [c38]Luís Moreira-Matias, João Mendes-Moreira, João Gama, Pavel Brazdil: Text Categorization Using an Ensemble Classifier Based on a Mean Co-association Matrix. MLDM 2012: 525-539
- 2010
- [c37]Gintare Grigonyte, João Cordeiro, Gaël Dias, Rumen Moraliyski, Pavel Brazdil: Paraphrase Alignment for Synonym Evidence Discovery. COLING 2010: 403-411
- [c36]
- [p3]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil: Meta-Learning - Concepts and Techniques. Data Mining and Knowledge Discovery Handbook 2010: 717-731
- [p2]Pavel Brazdil, Rui Leite: Determining the Best Classification Algorithm with Recourse to Sampling and Metalearning. Advances in Machine Learning I 2010: 173-188
- [r3]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares: Inductive Transfer. Encyclopedia of Machine Learning 2010: 545-548
- [r2]Pavel Brazdil, Ricardo Vilalta, Christophe G. Giraud-Carrier, Carlos Soares: Metalearning. Encyclopedia of Machine Learning 2010: 662-666
2000 – 2009
- 2009
- [b1]Pavel Brazdil, Christophe G. Giraud-Carrier, Carlos Soares, Ricardo Vilalta: Metalearning - Applications to Data Mining. Cognitive Technologies, Springer 2009, ISBN 978-3-540-73262-4, pp. I-X, 1-176
- [e5]João Gama, Vítor Santos Costa, Alípio Mário Jorge, Pavel Brazdil (Eds.): Discovery Science, 12th International Conference, DS 2009, Porto, Portugal, October 3-5, 2009. Lecture Notes in Computer Science 5808, Springer 2009, ISBN 978-3-642-04746-6
- [r1]Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares, Ricardo Vilalta: Meta-Learning. Encyclopedia of Data Warehousing and Mining 2009: 1207-1215
- 2007
- [j8]João Cordeiro, Gaël Dias, Pavel Brazdil: New Functions for Unsupervised Asymmetrical Paraphrase Detection. JSW 2(4): 12-23 (2007)
- [c35]Alberto Freitas, Altamiro da Costa Pereira, Pavel Brazdil: Cost-Sensitive Decision Trees Applied to Medical Data. DaWaK 2007: 303-312
- [c34]Rui Leite, Pavel Brazdil: An Iterative Process for Building Learning Curves and Predicting Relative Performance of Classifiers. EPIA Workshops 2007: 87-98
- [c33]João Cordeiro, Gaël Dias, Pavel Brazdil: Learning Paraphrases from WNS Corpora. FLAIRS Conference 2007: 193-198
- [c32]Fabrice Colas, Pavel Paclík, Joost N. Kok, Pavel Brazdil: Does SVM Really Scale Up to Large Bag of Words Feature Spaces? IDA 2007: 296-307
- 2006
- [c31]Fabrice Colas, Pavel Brazdil: Comparison of SVM and Some Older Classification Algorithms in Text Classification Tasks. IFIP AI 2006: 169-178
- [c30]Pedro Campos, Pavel Brazdil, Paula Brito: Organizational Survival In Cooperation Networks: The Case Of Automobile Manufacturing. PRO-VE 2006: 77-84
- [c29]Carlos Soares, Pavel Brazdil: Selecting parameters of SVM using meta-learning and kernel matrix-based meta-features. SAC 2006: 564-568
- [c28]Fabrice Colas, Pavel Brazdil: On the Behavior of SVM and Some Older Algorithms in Binary Text Classification Tasks. TSD 2006: 45-52
- 2005
- [c27]
- [p1]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil: Meta-Learning. The Data Mining and Knowledge Discovery Handbook 2005: 731-748
- [e4]João Gama, Rui Camacho, Pavel Brazdil, Alípio Jorge, Luís Torgo (Eds.): Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings. Lecture Notes in Computer Science 3720, Springer 2005, ISBN 3-540-29243-8
- [e3]Alípio Jorge, Luís Torgo, Pavel Brazdil, Rui Camacho, João Gama (Eds.): Knowledge Discovery in Databases: PKDD 2005, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings. Lecture Notes in Computer Science 3721, Springer 2005, ISBN 3-540-29244-6
- 2004
- [j7]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares: Using Meta-Learning to Support Data Mining. IJCSA 1(1): 31-45 (2004)
- [j6]Christophe G. Giraud-Carrier, Ricardo Vilalta, Pavel Brazdil: Introduction to the Special Issue on Meta-Learning. Machine Learning 54(3): 187-193 (2004)
- [j5]Carlos Soares, Pavel Brazdil, Petr Kuba: A Meta-Learning Method to Select the Kernel Width in Support Vector Regression. Machine Learning 54(3): 195-209 (2004)
- [c26]
- [c25]
- [c24]João Cordeiro, Pavel Brazdil: Learning Text Extraction Rules, without Ignoring Stop Words. PRIS 2004: 128-138
- 2003
- [j4]
- [j3]Pavel Brazdil, Carlos Soares, Joaquim Pinto da Costa: Ranking Learning Algorithms: Using IBL and Meta-Learning on Accuracy and Time Results. Machine Learning 50(3): 251-277 (2003)
- [c23]
- 2002
- [c22]Yonghong Peng, Peter A. Flach, Carlos Soares, Pavel Brazdil: Improved Dataset Characterisation for Meta-learning. Discovery Science 2002: 141-152
- [c21]Carlos Soares, Pavel Brazdil: A Comparative Study of Some Issues Concerning Algorithm Recommendation Using Ranking Methods. IBERAMIA 2002: 80-89
- 2001
- [c20]Rui Camacho, Pavel Brazdil: Improving the Robustness and Encoding Complexity of Behavioural Clones. ECML 2001: 37-48
- [c19]Pavel Brazdil, Carlos Soares, Rui Pereira: Reducing Rankings of Classifiers by Eliminating Redundant Classifiers. EPIA 2001: 14-21
- [c18]Carlos Soares, Johann Petrak, Pavel Brazdil: Sampling-Based Relative Landmarks: Systematically Test-Driving Algorithms Before Choosing. EPIA 2001: 88-95
- [c17]
- [e2]Pavel Brazdil, Alípio Jorge (Eds.): Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving, 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Porto, Portugal, December 17-20, 2001, Proceedings. Lecture Notes in Computer Science 2258, Springer 2001, ISBN 3-540-43030-X
- 2000
- [j2]
- [c16]Pavel Brazdil, Carlos Soares: A Comparison of Ranking Methods for Classification Algorithm Selection. ECML 2000: 63-74
- [c15]Carlos Soares, Pavel Brazdil: Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information. PKDD 2000: 126-135
1990 – 1999
- 1999
- [j1]
- 1998
- [c14]Alneu de Andrade Lopes, Pavel Brazdil: Redundant Covering with Global Evaluation in the RC1 Inductive Learner. SBIA 1998: 111-120
- 1996
- [c13]Alípio Jorge, Pavel Brazdil: Integrity Constraints in ILP Using a Monte Carlo Approach. Inductive Logic Programming Workshop 1996: 229-244
- 1995
- [c12]Alípio Jorge, Pavel Brazdil: Learning Recursion with Iterative Bootstrap Induction (Extended Abstract). ECML 1995: 299-302
- [c11]
- 1994
- [c10]
- [c9]Pavel Brazdil, Joao Gama, Bob Henery: Characterizing the Applicability of Classification Algorithms Using Meta-Level Learning. ECML 1994: 83-102
- 1993
- [e1]Pavel Brazdil (Ed.): Machine Learning: ECML-93, European Conference on Machine Learning, Vienna, Austria, April 5-7, 1993, Proceedings. Lecture Notes in Computer Science 667, Springer 1993, ISBN 3-540-56602-3
- 1992
- [c8]Pavel Brazdil: Approaches to Inductive Logic Programming. Advanced Topics in Artificial Intelligence 1992: 139-160
- [c7]Pavel Brazdil, Ivan Bruha: A Method of Processing Unknown Attribute Values by ID3. ICCI 1992: 253-256
- 1991
- [c6]Pavel Brazdil, Matjaz Gams, Sati S. Sian, Luís Torgo, Walter Van de Velde: Panel: Learning in Distributed Systems and Multi-Agent Environments. EWSL 1991: 412-423
- [c5]Pavel Brazdil, Stephen Muggleton: Learning to Relate Terms in a Multiple Agent Environment. EWSL 1991: 424-439
1980 – 1989
- 1987
- [c4]
- 1984
- [c3]
1970 – 1979
- 1978
- [c2]
- 1977
- [c1]
Coauthor Index
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last updated on 2013-10-02 11:08 CEST by the dblp team