Research Catalog

Title

Proceedings of the Tenth Annual Conference on Computational Learning Theory : July 6th-9th, 1997, Nashville, Tennessee / sponsored by Vanderbilt University in cooperation with ACM SIGACT and ACM SIGART.

Author

ACM Conference on Computational Learning Theory (10th : 1997 : Nashville, Tenn.)

Publication

New York, N.Y. : Association for Computer Machinery, [1997], ©1997.

Items in the Library & Off-site

Holdings

Details

Additional Authors

• ACM Special Interest Group for Automata and Computability Theory.
• SIGART.
• Vanderbilt University.

Description

vii, 338 pages : illustrations; 28 cm

Alternative Title

• COLT '97
• Proceedings of the 10th annual ACM Conference on Computational Learning Theory.
• COLT 97.

Subjects

• Artificial intelligence > Congresses
• Computational learning theory > Congresses

Note

• "ACM order number 604970"--P. [ii].

Bibliography (note)

• Includes bibliographical references and index.

Contents

• Information Theory in Probability, Statistics, Learning, and Neural Nets / Andrew Barron -- A PAC Analysis of a Bayesian Estimator / John Shawe-Taylor and Robert C. Williamson -- Learning Logic Programs by Using the Product Homomorphism Method / Tamas Horvdth, Robert H. Sloan and Gyorgy Turan -- On-line Evaluation and Prediction Using Linear Functions / Philip M. Long -- Derandomizing Stochastic Prediction Strategies / V. Vovk -- On-line Learning and the Metrical Task System Problem / Avrim Blum and Carl Burch -- On the Complexity of Learning for a Spiking Neuron / Wolfgang Maass and Michael Schmitt -- Learning Probabilistically Consistent Linear Threshold Functions / Tom Bylander -- PAC Adaptive Control of Linear Systems / Claude-Nicolas Fiechter -- FINite Learning Capabilities and Their Limits / Robert Daley and Bala Kalyanasundaram -- Asymmetric Team Learning / Kalvis Apsitis, Rusins Freivalds and Carl H. Smith --
• Generalized Notions of Mind Change Complexity / Arun Sharma, Frank Stephan and Yuri Ventsov -- A Brief Look at Some Machine Learning Problems in Genomics / David Haussler -- An Efficient Extension to Mixture Techniques for Prediction and Decision Trees / Fernando Pereira and Yoram Singer -- Performance Bounds for Nonlinear Time Series Prediction / Ron Meir -- Computational Sample Complexity / Scott Decatur, Oded Goldreich and Dana Ron -- Dense Shattering and Teaching Dimensions for Differentiable Families / A. Kowalczyk -- Algorithmic Stability and Sanity-check Bounds for Leave-one-out Cross-validation / Michael Kearns and Dana Ron -- Analysis of Two Gradient-based Algorithms for On-line Regression / Nicolo Cesa-Bianchi -- General Convergence Results for Linear Discriminant Updates / Adam J. Grove, Nick Littlestone and Dale Schuurmans -- The Binary Exponentiated Gradient Algorithm for Learning Linear Functions / Tom Bylander --
• A Dichotomy Theorem for Learning Quantified Boolean Formulas / Victor Dalmau -- Learning with Maximum-entropy Distributions / Yishay Mansour and Mariano Schain -- Generating All Maximal Independent Sets of Bounded-degree Hypergraphs / Nina Mishra and Leonard Pitt -- Some Label Efficient Learning Results / David Helmbold and Sandra Panizza -- Learning from Examples with Unspecified Attribute Values / Sally A. Goldman, Stephen S. Kwek and Stephen D. Scott -- Learning Distributions from Random Walks / Funda Ergun, S. Ravi Kumar and Ronitt Rubinfeld -- Distributed Cooperative Bayesian Learning Strategies / Kenji Yamanishi -- Resource Bounded Next Value and Explanatory Identification: Learning Automata, Patterns and Polynomials On-line / Susanne Kaufmann and Frank Stephan -- Inferring Answers to Queries / William I. Gasarch and Andrew C. Y. Lee -- Teachers, Learners and Black Boxes / Dana Angluin and Martins Krikis --
• Learning Markov Chains with Variable Memory Length from Noisy Output / Dana Angluin and Miklos Csuros -- Universal Portfolios with and without Transaction Costs / Avrim Blum and Adam Kalai -- Estimation of Time-varying Parameters in Statistical Models: An Optimization Approach / Dimitris Bertsimas, David Gamarnik and John N. Tsitsiklis -- Agnostic Learning of Geometric Patterns / Sally A. Goldman, Stephen S. Kwek and Stephen D. Scott.

ISBN

0897918916

OCLC

ocm37679735

Owning Institutions

Columbia University Libraries