Abstract is missing.
- Tailoring Representations to Different RequirementsKatharina Morik. 1-12 [doi]
- Theoretical Views of Boosting and ApplicationsRobert E. Schapire. 13-25 [doi]
- Extended Stochastic Complexity and Minimax Relative Loss AnalysisKenji Yamanishi. 26-38 [doi]
- Algebraic Analysis for Singular Statistical EstimationSumio Watanabe. 39-50 [doi]
- Generalization Error of Limear Neural Networks in Unidentifiable CasesKenji Fukumizu. 51-62 [doi]
- The Computational Limits to the Cognitive Power of the Neuroidal Tabula RasaJirí Wiedermann. 63-76 [doi]
- The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract)José L. Balcázar, Jorge Castro, David Guijarro, Hans-Ulrich Simon. 77-92 [doi]
- The VC-Dimension of Subclasses of PatternAndrew R. Mitchell, Tobias Scheffer, Arun Sharma, Frank Stephan. 93-105 [doi]
- On the V::gamma:: Dimension for Regression in Reproducing Kernel Hilbert SpacesTheodoros Evgeniou, Massimiliano Pontil. 106-117 [doi]
- On the Strength of Incremental LearningSteffen Lange, Gunter Grieser. 118-131 [doi]
- Learning from Random TextPeter Rossmanith. 132-144 [doi]
- Inductive Learning with CorroborationPhil Watson. 145-156 [doi]
- Flattening and ImplicationKouichi Hirata. 157-168 [doi]
- Induction of Logic Programs Based on psi-TermsYutaka Sasaki. 169-181 [doi]
- Complexity in the Case against Accuracy: When Building one Function-Free Horn Clause is as Hard as AnyRichard Nock. 182-193 [doi]
- A Method of Similarity-Driven Knowledge Revision for Type SpecializationsNobuhiro Morita, Makoto Haraguchi, Yoshiaki Okubo. 194-205 [doi]
- PAC Learning with Nasty NoiseNader H. Bshouty, Nadav Eiron, Eyal Kushilevitz. 206-218 [doi]
- Positive and Unlabeled Examples Help LearningFrancesco De Comité, François Denis, Rémi Gilleron, Fabien Letouzey. 219-230 [doi]
- Learning Real Polynomials with a Turing MachineDennis Cheung. 231-240 [doi]
- Faster Near-Optimal Reinforcement Learning: Adding Adaptiveness to the E:::3::: AlgorithmCarlos Domingo. 241-251 [doi]
- A Note on Support Vector Machine DegeneracyRyan M. Rifkin, Massimiliano Pontil, Alessandro Verri. 252-263 [doi]
- Learnability of Enumerable Classes of Recursive Functions from Typical ExamplesJochen Nessel. 264-275 [doi]
- On the Uniform Learnability of Approximations to Non-Recursive FunctionsFrank Stephan, Thomas Zeugmann. 276-290 [doi]
- Learning Minimal Covers of Functional Dependencies with QueriesMontserrat Hermo, Víctor Lavín. 291-300 [doi]
- Boolean Formulas are Hard to Learn for most Gate BasesVíctor Dalmau. 301-312 [doi]
- Finding Relevant Variables in PAC Model with Membership QueriesDavid Guijarro, Jun Tarui, Tatsuie Tsukiji. 313 [doi]
- Genral Linear Relations among Different Types of Predictive ComplexityYuri Kalnishkan. 323-334 [doi]
- Predicting Nearly as well as the best Pruning of a Planar Decision GraphEiji Takimoto, Manfred K. Warmuth. 335-346 [doi]
- On Learning Unions of Pattern Languages and Tree PatternsSally A. Goldman, Stephen Kwek. 347-363 [doi]