16. ALT 2005: Singapore

Sanjay Jain, Hans-Ulrich Simon, Etsuji Tomita (Eds.): Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 8-11, 2005, Proceedings. Lecture Notes in Computer Science 3734 Springer 2005, ISBN 3-540-29242-X BibTeX

Invited Papers

Gary Bradshaw:
Invention and Artificial Intelligence. 10
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Neil R. Smalheiser:
The Arrowsmith Project: 2005 Status Report. 11
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Ross D. King:
The Robot Scientist Project. 12
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Doina Caragea, Jun Zhang, Jie Bao, Jyotishman Pathak, Vasant Honavar:
Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. 13-44
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Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin:
Training Support Vector Machines via SMO-Type Decomposition Methods. 45-62
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Arthur Gretton, Olivier Bousquet, Alex J. Smola, Bernhard Schölkopf:
Measuring Statistical Dependence with Hilbert-Schmidt Norms. 63-77
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Adam Kowalczyk, Olivier Chapelle:
An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron. 78-91
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Yang Bo He, Zhi Geng, Xun Liang:
Learning Causal Structures Based on Markov Equivalence Class. 92-106
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Kazuho Watanabe, Sumio Watanabe:
Stochastic Complexity for Mixture of Exponential Families in Variational Bayes. 107-121
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Risivardhan Thonangi, Vikram Pudi:
ACME: An Associative Classifier Based on Maximum Entropy Principle. 122-134
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Jittat Fakcharoenphol, Boonserm Kijsirikul:
Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors. 135-147
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Daniil Ryabko:
On Computability of Pattern Recognition Problems. 148-156
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Nick Palmer, Paul W. Goldberg:
PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance. 157-170
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Omri Guttman, S. V. N. Vishwanathan, Robert C. Williamson:
Learnability of Probabilistic Automata via Oracles. 171-182
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Rotem Bennet, Nader H. Bshouty:
Learning Attribute-Efficiently with Corrupt Oracles. 183-197
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Wolfgang Lindner:
Learning DNF by Statistical and Proper Distance Queries Under the Uniform Distribution. 198-210
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Hirotaka Kato, Satoshi Matsumoto, Tetsuhiro Miyahara:
Learning of Elementary Formal Systems with Two Clauses Using Queries. 211-225
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Sanjay Jain, Steffen Lange, Sandra Zilles:
Gold-Style and Query Learning Under Various Constraints on the Target Class. 226-240
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Lorenzo Carlucci, John Case, Sanjay Jain, Frank Stephan:
Non U-Shaped Vacillatory and Team Learning. 241-255
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Sanjay Jain, Efim B. Kinber:
Learning Multiple Languages in Groups. 256-268
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Yen Kaow Ng, Takeshi Shinohara:
Inferring Unions of the Pattern Languages by the Most Fitting Covers. 269-282
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Alexander Clark, Rémi Eyraud:
Identification in the Limit of Substitutable Context-Free Languages. 283-296
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Henning Fernau:
Algorithms for Learning Regular Expressions. 297-311
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M. R. K. Krishna Rao:
A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data. 312-326
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Sanjay Jain, Eric Martin, Frank Stephan:
Absolute Versus Probabilistic Classification in a Logical Setting. 327-342
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Shigeaki Harada, Eiji Takimoto, Akira Maruoka:
Online Allocation with Risk Information. 343-355
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Jan Poland, Marcus Hutter:
Defensive Universal Learning with Experts. 356-370
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Jussi Kujala, Tapio Elomaa:
On Following the Perturbed Leader in the Bandit Setting. 371-385
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Matthew Henderson, John Shawe-Taylor, Janez Zerovnik:
Mixture of Vector Experts. 386-398
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Chris Mesterharm:
On-line Learning with Delayed Label Feedback. 399-413
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Alexey V. Chernov, Marcus Hutter:
Monotone Conditional Complexity Bounds on Future Prediction Errors. 414-428
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Vladimir Vovk:
Non-asymptotic Calibration and Resolution. 429-443
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Vladimir Vovk:
Defensive Prediction with Expert Advice. 444-458
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Vladimir Vovk, Ilia Nouretdinov, Akimichi Takemura, Glenn Shafer:
Defensive Forecasting for Linear Protocols. 459-473
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Frank J. Balbach, Thomas Zeugmann:
Teaching Learners with Restricted Mind Changes. 474-489
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