Abstract is missing.
- Editors IntroductionNicolò Cesa-Bianchi, Masayuki Numao, Rüdiger Reischuk. 1-6 [doi]
- Mathematics Based on LearningSusumu Hayashi. 7-21 [doi]
- Data Mining with Graphical ModelsRudolf Kruse, Christian Borgelt. 22 [doi]
- On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator EigenspectrumJohn Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola. 23-40 [doi]
- In Search of the Horowitz Factor: Interim Report on a Musical Discovery ProjectGerhard Widmer. 41 [doi]
- Learning Structure from Sequences, with Applications in a Digital LibraryIan H. Witten. 42-56 [doi]
- On Learning Monotone Boolean Functions under the Uniform DistributionKazuyuki Amano, Akira Maruoka. 57-68 [doi]
- On Learning Embedded Midbit FunctionsRocco A. Servedio. 69-82 [doi]
- Maximizing Agreements and CoAgnostic LearningNader H. Bshouty, Lynn Burroughs. 83-97 [doi]
- Optimally-Smooth Adaptive Boosting and Application to Agnostic LearningDmitry Gavinsky. 98-112 [doi]
- Large Margin Classification for Moving TargetsJyrki Kivinen, Alex J. Smola, Robert C. Williamson. 113-127 [doi]
- On the Smallest Possible Dimension and the Largest Possible Margin of Linear Arrangements Representing Given Concept Classes Uniform DistributionJürgen Forster, Hans-Ulrich Simon. 128-138 [doi]
- A General Dimension for Approximately Learning Boolean FunctionsJohannes Köbler, Wolfgang Lindner. 139-148 [doi]
- The Complexity of Learning Concept Classes with Polynomial General DimensionJohannes Köbler, Wolfgang Lindner. 149-163 [doi]
- On the Absence of Predictive Complexity for Some GamesYuri Kalnishkan, Michael V. Vyugin. 164-172 [doi]
- Consistency Queries in Information ExtractionGunter Grieser, Klaus P. Jantke, Steffen Lange. 173-187 [doi]
- Ordered Term Tree Languages which Are Polynomial Time Inductively Inferable from Positive DataYusuke Suzuki, Takayoshi Shoudai, Tomoyuki Uchida, Tetsuhiro Miyahara. 188-202 [doi]
- Reflective Inductive Inference of Recursive FunctionsGunter Grieser. 203-217 [doi]
- Classes with Easily Learnable SubclassesSanjay Jain, Wolfram Menzel, Frank Stephan. 218-232 [doi]
- On the Learnability of Vector SpacesValentina S. Harizanov, Frank Stephan. 233-247 [doi]
- Learning, Logic, and Topology in a Common FrameworkEric Martin, Arun Sharma, Frank Stephan. 248-262 [doi]
- A Pathology of Bottom-Up Hill-Climbing in Inductive Rule LearningJohannes Fürnkranz. 263-277 [doi]
- Minimised Residue Hypotheses in Relevant LogicBertram Fronhöfer, Akihiro Yamamoto. 278-292 [doi]
- Compactness and Learning of Classes of Unions of Erasing Regular Pattern LanguagesJin Uemura, Masako Sato. 293-307 [doi]
- A Negative Result on Inductive Inference of Extended Pattern LanguagesDaniel Reidenbach. 308-320 [doi]
- RBF Neural Networks and Descartes Rule of SignsMichael Schmitt. 321-335 [doi]
- Asymptotic Optimality of Transductive Confidence MachineVladimir Vovk. 336-350 [doi]
- An Efficient PAC Algorithm for Reconstructing a Mixture of LinesSanjoy Dasgupta, Elan Pavlov, Yoram Singer. 351-364 [doi]
- Constraint Classification: A New Approach to Multiclass ClassificationSariel Har-Peled, Dan Roth, Dav Zimak. 365-379 [doi]
- How to Achieve Minimax Expected Kullback-Leibler Distance from an Unknown Finite DistributionDietrich Braess, Jürgen Forster, Tomas Sauer, Hans-Ulrich Simon. 380-394 [doi]
- Classification with Intersecting RulesTony Lindgren, Henrik Boström. 395-402 [doi]
- Feedforward Neural Networks in Reinforcement Learning Applied to High-Dimensional Motor ControlRémi Coulom. 403-414 [doi]