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ORCID7th COLT 1994: New Brunswick, NJ, USA
- Manfred K. Warmuth:
Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, COLT 1994, New Brunswick, NJ, USA, July 12-15, 1994. ACM 1994, ISBN 0-89791-655-7 - Stephen H. Muggleton:
Bayesian Inductive Logic Programming. 3-11 - Fernando C. N. Pereira:
Frequencies vs Biases: Machine Learning Problems in Natural Language Processing (Extended Abstract). 12 - Michael I. Jordan:
A Statistical Approach to Decision Tree Modeling. 13-20 - Michael Frazier, Leonard Pitt:
CLASSIC Learning. 23-34 - Dana Ron
, Yoram Singer, Naftali Tishby:
Learning Probabilistic Automata with Variable Memory Length. 35-46 - Bhaskar DasGupta, Hava T. Siegelmann, Eduardo D. Sontag:
On a Learnability Question Associated to Neural Networks with Continuous Activations (Extended Abstract). 47-56 - Dana Angluin, Martins Krikis:
Learning with Malicious Membership Queries and Exceptions (Extended Abstract). 57-66 - Wolfgang Maass:
Efficient Agnostic PAC-Learning with Simple Hypothesis. 67-75 - David Haussler, H. Sebastian Seung, Michael J. Kearns, Naftali Tishby:
Rigorous Learning Curve Bounds from Statistical Mechanics. 76-87 - Claude-Nicolas Fiechter:
Efficient Reinforcement Learning. 88-97 - V. G. Vovk:
An Optimal-Control Application of Two Paradigms of On-Line Learning. 98-109 - Avrim Blum, Roni Khardon, Eyal Kushilevitz, Leonard Pitt, Dan Roth:
On Learning Read-k-Satisfy-j DNF. 110-117 - Krishnan Pillaipakkamnatt, Vijay Raghavan:
On the Limits of Proper Learnability of Subclasses of DNF Formulas. 118-129 - Nader H. Bshouty, Richard Cleve, Sampath Kannan, Christino Tamon:
Oracles and Queries that are Sufficient for Exact Learning (Extended Abstract). 130-139 - Andrey Burago:
Learning Structurally Reversible Context-Free Grammars from Queries and Counterexamples in Polynomial Time. 140-146 - David Gillman, Michael Sipser:
Inference and Minimization of Hidden Markov Chains. 147-158 - Joe Kilian, Kevin J. Lang, Barak A. Pearlmutter:
Playing the Matching-Shoulders Lob-Pass Game with Logarithmic Regret. 159-164 - Yoshifumi Sakai, Akira Maruoka:
Learning Monotone Log-Term DNF Formulas. 165-172 - Kenji Yamanishi:
The Minimum L-Complexity Algorithm and its Applications to Learning Non-Parametric Rules. 173-182 - Thomas H. Chung:
Approximate Methods for Sequential Decision Making Using Expert Advice. 183-189 - Rusins Freivalds, Marek Karpinski, Carl H. Smith:
Co-Learning of Total Recursive Functions. 190-197 - Paul W. Goldberg, Sally A. Goldman, H. David Mathias:
Learning Unions of Boxes with Membership and Equivalence Queries. 198-207 - José L. Balcázar, Josep Díaz, Ricard Gavaldà, Osamu Watanabe:
An Optimal Parallel Algorithm for Learning DFA. 208-217 - Zhixiang Chen, Steven Homer:
On Learning Counting Functions with Queries. 218-227 - Tibor Hegedüs:
Geometrical Concept Learning and Convex Polytopes. 228-236 - Robert H. Sloan, György Turán:
Learning with Queries but Incomplete Information (Extended Abstract). 237-245 - Paul W. Goldberg, Sally A. Goldman:
Learning One-Dimensional Geometric Patterns Under One-Sided Random Misclassification Noise. 246-255 - Steffen Lange:
The Representation of Recursive Languages and Its Impact on the Efficiency of Learning. 256-267 - Martin Kummer:
The Strength of Noninclusions for Teams of Finite Learners (Extended Abstract). 268-277 - Sanjay Jain, Arun Sharma:
On the Intrinsic Complexity of Language Identification. 278-286 - Martin Kummer, Frank Stephan:
Inclusion Problems in Parallel Learning and Games (Extended Abstract). 287-298 - Peter L. Bartlett, Philip M. Long, Robert C. Williamson:
Fat-Shattering and the Learnability of Real-Valued Functions. 299-310 - Daoud Bshouty, Nader H. Bshouty:
On Learning Arithmetic Read-Once Formulas with Exponentiation (Extended Abstract). 311-317 - Peter L. Bartlett, Paul Fischer, Klaus-Uwe Höffgen:
Exploiting Random Walks for Learning. 318-327 - Michael Frazier, Sally A. Goldman, Nina Mishra, Leonard Pitt:
Learning from a Consistently Ignorant Teacher. 328-339 - Tom Bylander:
Learning Linear Threshold Functions in the Presence of Classification Noise. 340-347 - Pascal Koiran:
Efficient Learning of Continuous Neural Networks. 348-355 - Kyung-Hoon Kwon, Kukjin Kang, Jong-Hoon Oh:
Generalization in Partially Connected Layered Neural Networks. 356-361 - Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson:
Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes. 362-367
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