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ORCID8th COLT 1995: Santa Cruz, California, USA
- Wolfgang Maass:
Proceedings of the Eigth Annual Conference on Computational Learning Theory, COLT 1995, Santa Cruz, California, USA, July 5-8, 1995. ACM 1995, ISBN 0-89791-723-5
Invited Talks
- Leslie G. Valiant:
Rationality. 3-14 - Terrence J. Sejnowski, Peter Dayan, P. Read Montague:
Predictive Hebbian Learning. 15-18
Session 1
- Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron:
An Experimental and Theoretical Comparison of Model Selection Methods. 21-30 - Dana Ron, Yoram Singer, Naftali Tishby:
On the Learnability and Usage of Acyclic Probabilistic Finite Automata. 31-40 - Yoav Freund, Dana Ron:
Learning to Model Sequences Generated by Switching Distributions. 41-50
Session 2
- V. G. Vovk:
A Game of Prediction with Expert Advice. 51-60 - David P. Helmbold, Robert E. Schapire:
Predicting Nearly as Well as the Best Pruning of a Decision Tree. 61-68 - David P. Helmbold, Yoram Singer, Robert E. Schapire, Manfred K. Warmuth:
A Comparison of New and Old Algorithms for a Mixture Estimation Problem. 69-78 - Nader H. Bshouty:
A Note on Learning Multivariate Polynomials Under the Uniform Distribution (Extended Abstract). 79-82 - Kenji Yamanishi:
Randomized Approximate Aggregating Strategies and Their Applications to Prediction and Discrimination. 83-90 - Olga Mitina, Nikolai K. Vereshchagin:
How to Use Expert Advice in the Case when Actual Values of Estimated Events Remain Unknown. 91-97
Session 3
- Avrim Blum, Prasad Chalasani, Sally A. Goldman, Donna K. Slonim:
Learning with Unreliable Boundary Queries. 98-107 - Tibor Hegedüs:
Generalized Teaching Dimensions and the Query Complexity of Learning. 108-117 - Nader H. Bshouty, Jeffrey C. Jackson:
Learning DNF over the Uniform Distribution using a Quantum Example Oracle. 118-127 - Yiqun Lisa Yin:
Reducing the Number of Queries in Self-Directed Learning. 128-135 - Shai Ben-David, Nadav Eiron, Eyal Kushilevitz:
On Self-Directed Learning. 136-143 - Ronald L. Rivest, Yiqun Lisa Yin:
Being Taught can be Faster than Asking Questions. 144-151
Session 4
- William I. Gasarch, Geoffrey R. Hird:
Reductions for Learning via Queries. 152-161 - Frank Stephan:
Learning via Queries and Oracles. 162-169 - Kalvis Apsitis, Rusins Freivalds, Carl H. Smith:
On the Inductive Inference of Real Valued Functions. 170-177 - Douglas A. Cenzer, William R. Moser:
Inductive Inference of Functions on the Rationals. 178-181 - Efim B. Kinber, Frank Stephan:
Language Learning from Texts: Mind Changes, Limited Memory and Monotonicity (Extended Abstract). 182-189 - Nader H. Bshouty, Christino Tamon, David K. Wilson:
On Learning Decision Trees with Large Output Domains (Extended Abstract). 190-197 - Nader H. Bshouty, Zhixiang Chen, Scott E. Decatur, Steven Homer:
On the Learnability of Zn-DNF Formulas (Extended Abstract). 198-205 - Yoshifumi Sakai, Eiji Takimoto, Akira Maruoka:
Proper Learning Algorithm for Functions of k Terms Under Smooth Distributions. 206-213 - Atsuyoshi Nakamura, Naoki Abe:
On-line Learning of Binary and n-ary Relations over Multi-dimensional Clusters. 214-221 - H. David Mathias:
DNF - If You Can't Learn'em, Teach'em: An Interactive Model of Teaching. 222-229
Session 5
- Eric B. Baum
, Dan Boneh, Charles Garrett:
On Genetic Algorithms. 230-239 - Jeong Han Kim, James R. Roche:
On the Optimal Capacity of Binary Neural Networks: Rigorous Combinatorial Approaches. 240-249 - Norbert Klasner, Hans Ulrich Simon:
From Noise-Free to Noise-Tolerant and from On-line to Batch Learning. 250-257 - John Shawe-Taylor:
Sample Sizes for Sigmoidal Neural Networks. 258-264 - Kim L. Blackmore, Robert C. Williamson, Iven M. Y. Mareels, William A. Sethares:
Online Learning via Congregational Gradient Descent. 265-272 - Changfeng Wang, Santosh S. Venkatesh:
Criteria for Specifying Machine Complexity in Learning. 273-280 - Lawrence K. Saul, Satinder P. Singh:
Markov Decision Processes in Large State Spaces. 281-288 - Jyrki Kivinen, Manfred K. Warmuth:
The Perceptron Algorithm vs. Winnow: Linear vs. Logarithmic Mistake Bounds when few Input Variables are Relevant. 289-296 - Kukjin Kang, Jong-Hoon Oh:
Learning by a Population of Perceptrons. 297-300
Session 6
- Roni Khardon, Dan Roth:
Learning to Reason with a Restricted View. 301-310 - Jonathan Baxter:
Learning Internal Representations. 311-320 - Baruch Awerbuch, Margrit Betke, Ronald L. Rivest, Mona Singh:
Piecemeal Graph Exploration by a Mobile Robot (Extended Abstract). 321-328 - David P. Dobkin, Dimitrios Gunopulos:
Concept Learning with Geometric Hypotheses. 329-336 - Paul Fischer:
More or Less Efficient Agnostic Learning of Convex Polygons. 337-344 - Nader H. Bshouty, Sally A. Goldman, H. David Mathias:
Noise-Tolerant Parallel Learning of Geometric Concepts. 345-352 - Scott E. Decatur, Rosario Gennaro:
On Learning from Noisy and Incomplete Examples. 353-360 - Funda Ergün, Ravi Kumar, Ronitt Rubinfeld:
On Learning Bounded-Width Branching Programs. 361-368 - Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson:
On Efficient Agnostic Learning of Linear Combinations of Basis Functions. 369-376 - Dale Schuurmans, Russell Greiner:
Sequential PAC Learning. 377-384 - Michael P. Perrone, Brian S. Blais:
Regression NSS: An Alternative to Cross Validation. 385-391
Session 7
- Peter L. Bartlett, Philip M. Long:
More Theorems about Scale-sensitive Dimensions and Learning. 392-401 - David Haussler, Manfred Opper:
General Bounds on the Mutual Information Between a Parameter and n Conditionally Independent Observations. 402-411 - Joel Ratsaby, Santosh S. Venkatesh:
Learning from a Mixture of Labeled and Unlabeled Examples with Parametric Side Information. 412-417 - Dan Boneh:
Learning Using Group Representations (Extended Abstract). 418-426
Session 8
- Dana Ron, Ronitt Rubinfeld:
Exactly Learning Automata with Small Cover Time. 427-436 - Javed A. Aslam, Scott E. Decatur:
Specification and Simulation of Statistical Query Algorithms for Efficiency and Noise Tolerance. 437-446 - Nader H. Bshouty:
Simple Learning Algorithms Using Divide and Conquer. 447-453 - Shai Ben-David, Leonid Gurvits:
A Note on VC-Dimension and Measures of Sets of Reals. 454-462
Corrigendum
- William W. Cohen, Haym Hirsh:
Corrigendum for "Learnability of Description Logics". COLT 1995: 463
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