COLT 1991

35 papers

A Geometric Approach to Threshold Circuit Complexity Vwani P. Roychowdhury, Kai-Yeung Siu, Alon Orlitsky, Thomas Kailath

A Loss Bound Model for On-Line Stochastic Prediction Strategies Kenji Yamanishi

Approximation and Estimation Bounds for Artificial Neural Networks Andrew R. Barron

Bounded Degree Graph Inference from Walks Vijay Raghavan

Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension David Haussler, Michael J. Kearns, Robert E. Schapire

Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron with Noise Manfred Opper, David Haussler

Evaluating the Performance of a Simple Inductive Procedure in the Presence of Overfitting Error Andrew B. Nobel

Fast Identification of Geometric Objects with Membership Queries William J. Bultman, Wolfgang Maass

Improved Learning of AC0 Functions Merrick L. Furst, Jeffrey C. Jackson, Sean W. Smith

Investigating the Distribution Assumptions in the Pac Learning Model Peter L. Bartlett, Robert C. Williamson

Learning 2µ DNF Formulas and Kµ Decision Trees Thomas R. Hancock

Learning and Generalization.(Abstract) Thomas M. Cover

Learning by Smoothing: A Morphological Approach Woonkyung Michael Kim

Learning Curves in Large Neural Networks H. Sebastian Seung, Haim Sompolinsky, Naftali Tishby

Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes Avrim Blum, Lisa Hellerstein, Nick Littlestone

Learning Monotone DNF with an Incomplete Membership Oracle Dana Angluin, Donna K. Slonim

Learning Monotone Kµ DNF Formulas on Product Distributions Thomas R. Hancock, Yishay Mansour

Learning Probabilistic Read-Once Formulas on Product Distributions Robert E. Schapire

Learning Read-Once Formulas over Fields and Extended Bases Thomas R. Hancock, Lisa Hellerstein

On Learning Binary Weights for Majority Functions Santosh S. Venkatesh

On the Complexity of Learning Strings and Sequences Tao Jiang, Ming Li

On the Complexity of Teaching Sally A. Goldman, Michael J. Kearns

On the Learnability of Infinitary Regular Sets Oded Maler, Amir Pnueli

On-Line Learning with an Oblivious Environment and the Power of Randomization Wolfgang Maass

Polynomial Learnability of Probabilistic Concepts with Respect to the Kullback-Leibler Divergence Naoki Abe, Manfred K. Warmuth, Jun'ichi Takeuchi

Polynomial-Time Learning of Very Simple Grammars from Positive Data Takashi Yokomori

Probably Almost Bayes Decisions Paul Fischer, Stefan Pölt, Hans Ulrich Simon

Redundant Noisy Attributes, Attribute Errors, and Linear-Threshold Learning Using Winnow Nick Littlestone

Relations Between Probabilistic and Team One-Shot Learners (Extended Abstract) Robert P. Daley, Leonard Pitt, Mahendran Velauthapillai, Todd Will

Simultaneous Learning of Concepts and Simultaneous Estimation of Probabilities Kevin Buescher, P. R. Kumar

The Correct Definition of Finite Elasticity: Corrigendum to Identification of Unions Tatsuya Motoki, Takeshi Shinohara, Keith Wright

The Role of Learning in Autonomous Robots Rodney A. Brooks

The VC-Dimension vs. the Statistical Capacity for Two Layer Networks with Binary Weights Chuanyi Ji, Demetri Psaltis

Tracking Drifting Concepts Using Random Examples David P. Helmbold, Philip M. Long

When Oracles Do Not Help Theodore A. Slaman, Robert Solovay