COLT 1988

31 papers

A General Lower Bound on the Number of Examples Needed for Learning Andrzej Ehrenfeucht, David Haussler, Michael J. Kearns, Leslie G. Valiant

Efficient Unsupervised Learning Philip D. Laird

Equivalence of Models for Polynomial Learnability David Haussler, Michael J. Kearns, Nick Littlestone, Manfred K. Warmuth

Functionality in Neural Nets Leslie G. Valiant

Inductive Inference: An Abstract Approach John C. Cherniavsky, Mahendran Velauthapillai, Richard Statman

Learnability by Fixed Distributions Gyora M. Benedek, Alon Itai

Learning Automata from Ordered Examples Sara Porat, Jerome A. Feldman

Learning Complicated Concepts Reliably and Usefully Ronald L. Rivest, Robert Sloan

Learning Context-Free Grammars from Structural Data in Polynomial Time Yasubumi Sakakibara

Learning Decision Trees from Random Examples Andrzej Ehrenfeucht, David Haussler

Learning in Neural Networks J. Stephen Judd

Learning in Parallel Jeffrey Scott Vitter, Jyh-Han Lin

Learning in Threshold Networks P. Raghavan

Learning K-DNF with Noise in the Attributes George Shackelford, Dennis Volper

Learning Pattern Languages from a Single Initial Example and from Queries Assaf Marron

Learning Probabilistic Prediction Functions Alfredo De Santis, George Markowsky, Mark N. Wegman

Learning Programs with an Easy to Calculate Set of Errors William I. Gasarch, Ramesh K. Sitaraman, Carl H. Smith, Mahendran Velauthapillai

Learning Regular Languages from Counterexamples Oscar H. Ibarra, Tao Jiang

Learning Theories in a Subset of a Polyadic Logic Ranan B. Banerji

Learning via Queries William I. Gasarch, Carl H. Smith

Learning with Hints Dana Angluin

Non-Learnable Classes of Boolean Formulae That Are Closer Under Variable Permutation Haim Schweitzer

On the Learnability of Finite Automata Ming Li, Umesh V. Vazirani

Predicting 0, 1-Functions on Randomly Drawn Points David Haussler, Nick Littlestone, Manfred K. Warmuth

Prudence in Language Learning Stuart A. Kurtz, James S. Royer

Results on Learnability and the Vapnick-Chervonenkis Dimension Nathan Linial, Yishay Mansour, Ronald L. Rivest

Some Remarks About Space-Complexity of Learning, and Circuit Complexity of Recognizing Stéphane Boucheron, Jean Sallantin

The Power of Vacillation John Case

Training a 3-Node Neural Network Is NP-Complete Avrim Blum, Ronald L. Rivest

Transformation of Probabilistic Learning Strategies into Deterministic Learning Strategies Robert P. Daley

Types of Noise in Data for Concept Learning Robert Sloan