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ORCID16. ALT 2005: Singapore
- Sanjay Jain, Hans Ulrich Simon
, Etsuji Tomita:
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 - Sanjay Jain, Hans Ulrich Simon, Etsuji Tomita:
Editors' Introduction. 1-9
Invited Papers
- Gary Bradshaw:
Invention and Artificial Intelligence. 10 - Neil R. Smalheiser:
The Arrowsmith Project: 2005 Status Report. 11 - Ross D. King:
The Robot Scientist Project. 12 - Doina Caragea, Jun Zhang, Jie Bao, Jyotishman Pathak, Vasant G. Honavar:
Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. 13-44 - Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin:
Training Support Vector Machines via SMO-Type Decomposition Methods. 45-62
Kernel-Based Learning
- Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf:
Measuring Statistical Dependence with Hilbert-Schmidt Norms. 63-77 - Adam Kowalczyk, Olivier Chapelle:
An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron. 78-91
Bayesian and Statistical Models
- Yang Bo He, Zhi Geng, Xun Liang:
Learning Causal Structures Based on Markov Equivalence Class. 92-106 - Kazuho Watanabe, Sumio Watanabe:
Stochastic Complexity for Mixture of Exponential Families in Variational Bayes. 107-121 - Risivardhan Thonangi, Vikram Pudi:
ACME: An Associative Classifier Based on Maximum Entropy Principle. 122-134
PAC-Learning
- Jittat Fakcharoenphol, Boonserm Kijsirikul:
Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors. 135-147 - Daniil Ryabko:
On Computability of Pattern Recognition Problems. 148-156 - Nick Palmer, Paul W. Goldberg:
PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance. 157-170 - Omri Guttman, S. V. N. Vishwanathan, Robert C. Williamson:
Learnability of Probabilistic Automata via Oracles. 171-182
Query-Learning
- Rotem Bennet, Nader H. Bshouty:
Learning Attribute-Efficiently with Corrupt Oracles. 183-197 - Wolfgang Lindner:
Learning DNF by Statistical and Proper Distance Queries Under the Uniform Distribution. 198-210 - Hirotaka Kato, Satoshi Matsumoto, Tetsuhiro Miyahara:
Learning of Elementary Formal Systems with Two Clauses Using Queries. 211-225 - Sanjay Jain, Steffen Lange, Sandra Zilles:
Gold-Style and Query Learning Under Various Constraints on the Target Class. 226-240
Inductive Inference
- Lorenzo Carlucci, John Case, Sanjay Jain, Frank Stephan:
Non U-Shaped Vacillatory and Team Learning. 241-255 - Sanjay Jain, Efim B. Kinber:
Learning Multiple Languages in Groups. 256-268
Language Learning
- Yen Kaow Ng, Takeshi Shinohara:
Inferring Unions of the Pattern Languages by the Most Fitting Covers. 269-282 - Alexander Clark, Rémi Eyraud:
Identification in the Limit of Substitutable Context-Free Languages. 283-296 - Henning Fernau:
Algorithms for Learning Regular Expressions. 297-311
Learning and Logic
- M. R. K. Krishna Rao:
A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data. 312-326 - Sanjay Jain, Eric Martin, Frank Stephan:
Absolute Versus Probabilistic Classification in a Logical Setting. 327-342
Learning from Expert Advice
- Shigeaki Harada, Eiji Takimoto, Akira Maruoka:
Online Allocation with Risk Information. 343-355 - Jan Poland, Marcus Hutter:
Defensive Universal Learning with Experts. 356-370 - Jussi Kujala, Tapio Elomaa:
On Following the Perturbed Leader in the Bandit Setting. 371-385 - Matthew Henderson, John Shawe-Taylor, Janez Zerovnik:
Mixture of Vector Experts. 386-398
Online Learning
- Chris Mesterharm:
On-line Learning with Delayed Label Feedback. 399-413 - Alexey V. Chernov, Marcus Hutter:
Monotone Conditional Complexity Bounds on Future Prediction Errors. 414-428
Defensive Forecasting
- Vladimir Vovk:
Non-asymptotic Calibration and Resolution. 429-443 - Vladimir Vovk:
Defensive Prediction with Expert Advice. 444-458 - Vladimir Vovk, Ilia Nouretdinov, Akimichi Takemura, Glenn Shafer:
Defensive Forecasting for Linear Protocols. 459-473
Teaching
- Frank J. Balbach, Thomas Zeugmann:
Teaching Learners with Restricted Mind Changes. 474-489
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