7. COLT 1994:
New Brunswick, NJ, USA
Manfred K. Warmuth (Ed.):
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 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 V. 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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