Abstract is missing.
- Program Error Detection/Correction: Turning PAC Learning into PERFECT Learning (Abstract)Manuel Blum. 1
- Team Learning as a GameAndris Ambainis, Kalvis Apsitis, Rusins Freivalds, William I. Gasarch, Carl H. Smith. 2-17
- Inferability of Recursive Real-Valued FunctionsEiju Hirowatari, Setsuo Arikawa. 18-31
- Learning of R.E. Languages from Good ExamplesSanjay Jain, Steffen Lange, Jochen Nessel. 32-47
- Identifiability of Subspaces and Homomorphic Images of Zero-Reversible LanguagesSatoshi Kobayashi, Takashi Yokomori. 48-61
- On Exploiting Knowledge and Concept Use in Learning TheoryLeonard Pitt. 62-84
- Partial Occam s Razor and Its ApplicationsCarlos Domingo, Tatsuie Tsukiji, Osamu Watanabe. 85-99
- Deranomized Learning of Boolean FunctionsMeera Sitharam, Timothy Straney. 100-115
- Learning DFA from Simple ExamplesRajesh Parekh, Vasant Honavar. 116-131
- PAC Learning under Helpful DistributionsFrançois Denis, Rémi Gilleron. 132-145
- PAC Learning Using Nadaraya-Watson Estimator Based on Orthonormal SystemsHongzhu Qiao, Nageswara S. V. Rao, Vladimir Protopopescu. 146-160
- Monotone Extensions of Boolean Data SetsEndre Boros, Toshihide Ibaraki, Kazuhisa Makino. 161-175
- Classical Brouwer-Heyting-Kolmogorov InterpretationMasahiko Sato. 176-196
- Inferring a System from Examples with Time PassageYasuhito Mukouchi. 197-211
- Polynomial Time Inductive Inference of Regular Term Tree Languages from Positive DataSatoshi Matsumoto, Yukiko Hayashi, Takayoshi Shoudai. 212-227
- Synthesizing Noise-Tolerant Language LearnersJohn Case, Sanjay Jain, Arun Sharma. 228-243
- Effects of Kolmogorov Complexity Present in Inductive Inference as WellAndris Ambainis, Kalvis Apsitis, Cristian Calude, Rusins Freivalds, Marek Karpinski, Tomas Larfeldt, Iveta Sala, Juris Smotrovs. 244-259
- Learning One-Variable Pattern Languages Very Efficiently on Average, in Parallel, and by Asking QueriesThomas Erlebach, Peter Rossmanith, Hans Stadtherr, Angelika Steger, Thomas Zeugmann. 260-276
- Oracles in Sigma:::::::p:::::::::2:: are Sufficient for Exact LearningJohannes Köbler, Wolfgang Lindner. 277-290
- Exact Learning via Teaching Assistants (Extended Abstract)Vikraman Arvind, N. V. Vinodchandran. 291-306
- An Efficient Exact Learning Algorithm for Ordered Binary Decision DiagramsAtsuyoshi Nakamura. 307-322
- Probability Theory for the Brier GameV. G. Vovk. 323-338
- Learning and Revising Theories in Noisy DomainsXiaolong Zhang, Masayuki Numao. 339-351
- A Note on a Scale-Sensitive Dimension of Linear Bounded Functionals in Banach SpacesLeonid Gurvits. 352-363
- On the Relevance of Time in Neural Computation and LearningWolfgang Maass. 364-384
- A Simple Algorithm for Predicting Nearly as Well as the Best Pruning Labeled with the Best Prediction Values of a Decision TreeEiji Takimoto, Ken ichi Hirai, Akira Maruoka. 385-400
- Learning Disjunctions of FeaturesStephen Kwek. 401-415
- Learning Simple Deterministic Finite-Memory AutomataHiroshi Sakamoto. 416-431
- Learning Acyclic First-Order Horn Sentences from EntailmentHiroki Arimura. 432-445
- On Learning Disjunctions of Zero-One Treshold Functions with QueriesTibor Hegedüs, Piotr Indyk. 446-460