Algorithmic learning theory. 13th international conference, ALT 2002, Lübeck, Germany, November 24--26, 2002. Proceedings
The articles of this volume will be reviewed individually. The preceding conference (12th) has been reviewed (see Zbl 0983.00054). Indexed articles: \textit{Cesa-Bianchi, Nicolò; Numao, Masayuki; Reischuk, Rüdiger}, Editors' introduction, 1-6 [Zbl 1024.68530] \textit{Hayashi, Susumu}, Mathematics based on learning, 7-21 [Zbl 1024.68052] \textit{Kruse, Rudolf; Borgelt, Christian}, Data mining with graphical models, 22 [Zbl 1024.68525] \textit{Shawe-Taylor, John; Williams, Chris; Cristianini, Nello; Kandola, Jaz}, On the eigenspectrum of the Gram matrix and its relationship to the operator eigenspectrum, 23-40 [Zbl 1024.68060] \textit{Widmer, Gerhard}, In search of the Horowitz factor: Interim report on a musical discovery project, 41 [Zbl 1024.68540] \textit{Witten, Ian H.}, Learning structure from sequences, with applications in a digital library, 42-56 [Zbl 1024.68542] \textit{Amano, Kazuyuki; Maruoka, Akira}, On learning monotone Boolean functions under the uniform distribution, 57-68 [Zbl 1024.68046] \textit{Servedio, Rocco A.}, On learning embedded midbit functions, 69-82 [Zbl 1024.68059] \textit{Bshouty, Nader H.; Burroughs, Lynn}, Maximizing agreements and CoAgnostic learning, 83-97 [Zbl 1024.68048] \textit{Gavinsky, Dmitry}, Optimally-smooth adaptive boosting and application to agnostic learning, 98-112 [Zbl 1024.68533] \textit{Kivinen, Jyrki; Smola, Alex J.; Williamson, Robert C.}, Large margin classification for moving targets, 113-127 [Zbl 1024.68054] \textit{Forster, Jürgen; Simon, Hans Ulrich}, On the smallest possible dimension and the largest possible margin of linear arrangements representing given concept classes uniform distribution, 128-138 [Zbl 1024.68049] \textit{Köbler, Johannes; Lindner, Wolfgang}, A general dimension for approximately learning Boolean functions, 139-148 [Zbl 1024.68055] \textit{Köbler, Johannes; Lindner, Wolfgang}, The complexity of learning concept classes with polynomial general dimension, 149-163 [Zbl 1024.68056] \textit{Kalnishkan, Yuri; Vyugin, Michael V.}, On the absence of predictive complexity for some games, 164-172 [Zbl 1024.68536] \textit{Grieser, Gunter; Jantke, Klaus P.; Lange, Steffen}, Consistency queries in information extraction, 173-187 [Zbl 1024.68534] \textit{Suzuki, Yusuke; Shoudai, Takayoshi; Uchida, Tomoyuki; Miyahara, Tetsuhiro}, Ordered term tree languages which are polynomial time inductively inferable from positive data, 188-202 [Zbl 1024.68061] \textit{Grieser, Gunter}, Reflective inductive inference of recursive functions, 203-217 [Zbl 1024.68050] \textit{Jain, Sanjay; Menzel, Wolfram; Stephan, Frank}, Classes with easily learnable subclasses, 218-232 [Zbl 1024.68053] \textit{Harizanov, Valentina S.; Stephan, Frank}, On the learnability of vector spaces, 233-247 [Zbl 1024.68051] \textit{Martin, Eric; Sharma, Arun; Stephan, Frank}, Learning, logic, and topology in a common framework, 248-262 [Zbl 1024.68057] \textit{Fürnkranz, Johannes}, A pathology of bottom-up hill-climbing in inductive rule learning, 263-277 [Zbl 1024.68532] \textit{Fronhöfer, Bertram; Yamamoto, Akihiro}, Minimised residue hypotheses in relevant logic, 278-292 [Zbl 1024.03021] \textit{Uemura, Jin; Sato, Masako}, Compactness and learning of classes of unions of erasing regular pattern languages, 293-307 [Zbl 1024.68062] \textit{Reidenbach, Daniel}, A negative result on inductive inference of extended pattern languages, 308-320 [Zbl 1024.68058] \textit{Schmitt, Michael}, RBF neural networks and Descartes' rule of signs, 321-335 [Zbl 1024.68084] \textit{Vovk, Vladimir}, Asymptotic optimality of transductive confidence machine, 336-350 [Zbl 1024.68085] \textit{Dasgupta, Sanjoy; Pavlov, Elan; Singer, Yoram}, An efficient PAC algorithm for reconstructing a mixture of lines, 351-364 [Zbl 1024.68531] \textit{Har-Peled, Sariel; Roth, Dan; Zimak, Dav}, Constraint classification: A new approach to multiclass classification, 365-379 [Zbl 1024.68081] \textit{Braess, Dietrich; Forster, Jürgen; Sauer, Tomas; Simon, Hans U.}, How to achieve minimax expected Kullback-Leibler distance from an unknown finite distribution, 380-394 [Zbl 1024.68047] \textit{Lindgren, Tony; Boström, Henrik}, Classification with intersecting rules, 395-402 [Zbl 1024.68537] \textit{Coulom, Rémi}, Feedforward neural networks in reinforcement learning applied to high-dimensional motor control, 403-413 [Zbl 1024.68546]
scientific article; zbMATH DE number 1911149