Machine learning: ECML 2002. 13th European conference, Helsinki, Finland, August 19--23, 2002. Proceedings (Q1848548)

The articles of mathematical interest will be reviewed individually. The preceding conference (12th, 2001) has been reviewed (see Zbl 0971.00049). Indexed articles: \textit{Banerjee, Bikramjit; Peng, Jing}, Convergent gradient ascent in general-sum games, 1-9 [Zbl 1014.68131] \textit{Bay, Stephen D.; Shapiro, Daniel G.; Langley, Pat}, Revising engineering models: Combining computational discovery with knowledge, 10-22 [Zbl 1014.93500] \textit{Buntine, Wray}, Variational extensions to EM and multinomial PCA, 23-34 [Zbl 1014.68524] \textit{Carreras, Xavier; Màrquez, Lluís; Punyakanok, Vasin; Roth, Dan}, Learning and inference for clause identification, 35-47 [Zbl 1014.68515] \textit{Dai, Honghua; Li, Gang; Tu, Yiqing}, An empirical study of encoding schemes and search strategies in discovering causal networks, 48-59 [Zbl 1014.68525] \textit{Derbeko, Philip; El-Yaniv, Ran; Meir, Ron}, Variance optimized bagging, 60-71 [Zbl 1014.68909] \textit{Eibl, Günther; Pfeiffer, Karl Peter}, How to make AdaBoost. M1 work for weak base classifiers by changing only one line of the code, 72-83 [Zbl 1014.68933] \textit{Engel, Yaakov; Mannor, Shie; Meir, Ron}, Sparse online greedy support vector regression, 84-96 [Zbl 1014.68849] \textit{Fürnkranz, Johannes}, Pairwise classification as an ensemble technique, 97-110 [Zbl 1014.68779] \textit{Góra, Grzegorz; Wojna, Arkadiusz}, RIONA: A classifier combining rule induction and k-NN method with automated selection of optimal neighbourhood, 111-123 [Zbl 1014.68948] \textit{Halck, Ole Martin}, Using hard classifiers to estimate conditional class probabilities, 124-134 [Zbl 1014.68900] \textit{Harris, Harlan D.}, Evidence that incremental Delta-Bar-Delta is an attribute-efficient linear learner, 135-147 [Zbl 1014.68955] \textit{Hoche, Susanne; Wrobel, Stefan}, Scaling boosting by margin-based inclusionof features and relations, 148-160 [Zbl 1014.68832] \textit{Holmes, Geoffrey; Pfahringer, Bernhard; Kirkby, Richard; Frank, Eibe; Hall, Mark}, Multiclass alternating decision trees, 161-172 [Zbl 1014.68754] \textit{Hüllermeier, Eyke}, Possibilistic induction in decision-tree learning, 173-184 [Zbl 1014.68520] \textit{Kermorvant, Christopher; Dupont, Pierre}, Improved smoothing for probabilistic suffix trees seen as variable order Markov chains, 185-194 [Zbl 1014.68946] \textit{Klink, Stefan; Hust, Armin; Junker, Markus; Dengel, Andreas}, Collaborative learning of term-based concepts for automatic query expansion, 195-206 [Zbl 1014.68630] \textit{Kråkenes, Tony; Halck, Ole Martin}, Learning to play a highly complex game from human expert games, 207-218 [Zbl 1014.68517] \textit{Kukar, Matjaz; Kononenko, Igor}, Reliable classifications with machine learning, 219-231 [Zbl 1014.68805] \textit{Kushmerick, Nicholas}, Robustness analyses of instance-based collaborative recommendation, 232-244 [Zbl 1014.68522] \textit{Kwek, Stephen; Nguyen, Chau}, iBoost: Boosting using an instance-based exponential weighting scheme, 245-257 [Zbl 1014.68709] \textit{Ludl, Marcus-Christopher; Widmer, Gerhard}, Towards a simple clustering criterion based on minimum length encoding, 258-269 [Zbl 1014.68895] \textit{Margineantu, Dragos D.}, Class probability estimation and cost-sensitive classification decisions, 270-281 [Zbl 1014.68622] \textit{Martin, Mario}, On-line support vector machine regression, 282-294 [Zbl 1014.68133] \textit{Menache, Ishai; Mannor, Shie; Shimkin, Nahum}, Q-cut -- dynamic discovery of sub-goals in reinforcement learning, 295-306 [Zbl 1014.68796] \textit{Morik, Katharina; Rüping, Stefan}, A multistrategy approach to the classification of phases in business cycles, 307-318 [Zbl 1014.68570] \textit{Nock, Richard; Lefaucheur, Patrice}, A robust boosting algorithm, 319-330 [Zbl 1014.68509] \textit{Ontañón, Santiago; Plaza, Enric}, Case exchange strategies in multiagent learning, 331-344 [Zbl 1014.68619] \textit{Papadopoulos, Harris; Proedrou, Kostas; Vovk, Volodya; Gammerman, Alex}, Inductive confidence machines for regression, 345-356 [Zbl 1014.68514] \textit{Peña Castillo, Lourdes; Wrobel, Stefan}, Macro-operators in multirelational learning: A search-space reduction technique, 357-368 [Zbl 1014.68132] \textit{Preux, Philippe}, Propagation of \(Q\)-values in tabular TD\((\lambda)\), 369-380 [Zbl 1014.68521] \textit{Proedrou, Kostas; Nouretdinov, Ilia; Vovk, Volodya; Gammerman, Alex}, Transductive confidence machines for pattern recognition, 381-390 [Zbl 1014.68527] \textit{Ratitch, Bohdana; Precup, Doina}, Characterizing Markov decision processes, 391-404 [Zbl 1014.68620] \textit{Rückert, Ulrich; Kramer, Stefan; De Raedt, Luc}, Phase transitions and stochastic local search in k-term DNF learning, 405-417 [Zbl 1014.68519] \textit{Sinkkonen, Janne; Kaski, Samuel; Nikkilä, Janne}, Discriminative clustering: Optimal contingency tables by learning metrics, 418-430 [Zbl 1014.68512] \textit{Thollard, Franck; Sebban, Marc; Ezequel, Philippe}, Boosting density function estimators, 431-443 [Zbl 1014.68510] \textit{Todorovski, Ljupco; Blockeel, Hendrik; Dzeroski, Sašo}, Ranking with predictive clustering trees, 444-455 [Zbl 1014.68798] \textit{Tsochantaridis, Ioannis; Hofmann, Thomas}, Support vector machines for polycategorical classification, 456-467 [Zbl 1014.68523] \textit{Vittaut, Jean-Noël; Amini, Massih-Reza; Gallinari, Patrick}, Learning classification with both labeled and unlabeled data, 468-479 [Zbl 1014.68516] \textit{Yeang, Chen-Hsiang}, An information geometric perspective on active learning, 480-492 [Zbl 1014.68130] \textit{Ženko, Bernard; Džeroski, Sašo}, Stacking with an extended set of meta-level attributes and MLR, 493-504 [Zbl 1014.68851] \textit{Oja, Erkki}, Finding hidden factors using independent component analysis, 505 [Zbl 1014.68685] \textit{Roth, Dan}, Reasoning with classifiers, 506-510 [Zbl 1014.68800] \textit{Schölkopf, Bernhard; Weston, Jason; Eskin, Eleazar; Leslie, Christina; Stafford Noble, William}, A kernel approach for learning from almost orthogonal patterns, 511-528 [Zbl 1014.68129] \textit{Smyth, Padhraic}, Learning with mixture models: Concepts and applications, 529 [Zbl 1014.68733]