10. ALT 1999: Tokyo, Japan

@proceedings{DBLP:conf/alt/1999,
  editor    = {Osamu Watanabe and
               Takashi Yokomori},
  title     = {Algorithmic Learning Theory, 10th International Conference, ALT
               '99, Tokyo, Japan, December 6-8, 1999, Proceedings},
  booktitle = {ALT},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {1720},
  year      = {1999},
  isbn      = {3-540-66748-2},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Invited Lectures

• Katharina Morik:
  Tailoring Representations to Different Requirements. 1-12
  Electronic Edition (Springer LINK) BibTeX
• Robert E. Schapire:
  Theoretical Views of Boosting and Applications. 13-25
  Electronic Edition (Springer LINK) BibTeX
• Kenji Yamanishi:
  Extended Stochastic Complexity and Minimax Relative Loss Analysis. 26-38
  Electronic Edition (Springer LINK) BibTeX

Regular Contributions

Neural Networks

• Sumio Watanabe:
  Algebraic Analysis for Singular Statistical Estimation. 39-50
  Electronic Edition (Springer LINK) BibTeX
• Kenji Fukumizu:
  Generalization Error of Limear Neural Networks in Unidentifiable Cases. 51-62
  Electronic Edition (Springer LINK) BibTeX
• Jirí Wiedermann:
  The Computational Limits to the Cognitive Power of the Neuroidal Tabula Rasa. 63-76
  Electronic Edition (Springer LINK) BibTeX

Learning Dimension

• José L. Balcázar, Jorge Castro, David Guijarro, Hans-Ulrich Simon:
  The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract). 77-92
  Electronic Edition (Springer LINK) BibTeX
• Andrew R. Mitchell, Tobias Scheffer, Arun Sharma, Frank Stephan:
  The VC-Dimension of Subclasses of Pattern. 93-105
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• Theodoros Evgeniou, Massimiliano Pontil:
  On the V_gamma Dimension for Regression in Reproducing Kernel Hilbert Spaces. 106-117
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Inductive Inference

• Steffen Lange, Gunter Grieser:
  On the Strength of Incremental Learning. 118-131
  Electronic Edition (Springer LINK) BibTeX
• Peter Rossmanith:
  Learning from Random Text. 132-144
  Electronic Edition (Springer LINK) BibTeX
• Phil Watson:
  Inductive Learning with Corroboration. 145-156
  Electronic Edition (Springer LINK) BibTeX

Inductive Logic Programming

• Kouichi Hirata:
  Flattening and Implication. 157-168
  Electronic Edition (Springer LINK) BibTeX
• Yutaka Sasaki:
  Induction of Logic Programs Based on psi-Terms. 169-181
  Electronic Edition (Springer LINK) BibTeX
• Richard Nock:
  Complexity in the Case against Accuracy: When Building one Function-Free Horn Clause is as Hard as Any. 182-193
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• Nobuhiro Morita, Makoto Haraguchi, Yoshiaki Okubo:
  A Method of Similarity-Driven Knowledge Revision for Type Specializations. 194-205
  Electronic Edition (Springer LINK) BibTeX

PAC Learning

• Nader H. Bshouty, Nadav Eiron, Eyal Kushilevitz:
  PAC Learning with Nasty Noise. 206-218
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• Francesco De Comité, François Denis, Rémi Gilleron, Fabien Letouzey:
  Positive and Unlabeled Examples Help Learning. 219-230
  Electronic Edition (Springer LINK) BibTeX
• Dennis Cheung:
  Learning Real Polynomials with a Turing Machine. 231-240
  Electronic Edition (Springer LINK) BibTeX

Mathematical Tools for Learning

• Carlos Domingo:
  Faster Near-Optimal Reinforcement Learning: Adding Adaptiveness to the E³ Algorithm. 241-251
  Electronic Edition (Springer LINK) BibTeX
• Ryan M. Rifkin, Massimiliano Pontil, Alessandro Verri:
  A Note on Support Vector Machine Degeneracy. 252-263
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Learning Recursive Functions

• Jochen Nessel:
  Learnability of Enumerable Classes of Recursive Functions from "Typical" Examples. 264-275
  Electronic Edition (Springer LINK) BibTeX
• Frank Stephan, Thomas Zeugmann:
  On the Uniform Learnability of Approximations to Non-Recursive Functions. 276-290
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Query Learning

• Montserrat Hermo, Víctor Lavín:
  Learning Minimal Covers of Functional Dependencies with Queries. 291-300
  Electronic Edition (Springer LINK) BibTeX
• Víctor Dalmau:
  Boolean Formulas are Hard to Learn for most Gate Bases. 301-312
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• David Guijarro, Jun Tarui, Tatsuie Tsukiji:
  Finding Relevant Variables in PAC Model with Membership Queries. 313-
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On-Line Learning

• Yuri Kalnishkan:
  Genral Linear Relations among Different Types of Predictive Complexity. 323-334
  Electronic Edition (Springer LINK) BibTeX
• Eiji Takimoto, Manfred K. Warmuth:
  Predicting Nearly as well as the best Pruning of a Planar Decision Graph. 335-346
  Electronic Edition (Springer LINK) BibTeX
• Sally A. Goldman, Stephen Kwek:
  On Learning Unions of Pattern Languages and Tree Patterns. 347-363
  Electronic Edition (Springer LINK) BibTeX