Revising threshold functions

Authors:
Robert H. Sloan;Balázs Szörényi;György Turán
Affiliations:
Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60607-7053, USA;Research Group on Artificial Intelligence, Hungarian Academy of Sciences and University of Szeged, Szeged, 6720, Hungary;Department of Mathematics, Statistics and Computer Science, University of Illinois at Chicago, Chicago, IL 60607-7045, USA and Research Group on Artificial Intelligence, Hungarian Academy of Scien ...
Venue:
Theoretical Computer Science
Year:
2007

Citing 22
Cited 0

Computational limitations on learning from examples

Journal of the ACM (JACM)
Lower Bound Methods and Separation Results for On-Line Learning Models

Machine Learning - Computational learning theory
Extracting Refined Rules from Knowledge-Based Neural Networks

Machine Learning
Theory refinement combining analytical and empirical methods

Artificial Intelligence
Automated Refinement of First-Order Horn-Clause Domain Theories

Machine Learning
Learning in the presence of finitely or infinitely many irrelevant attributes

Journal of Computer and System Sciences
On training simple neural networks and small-weight neurons

Euro-COLT '93 Proceedings of the first European conference on Computational learning theory
Attribute-efficient learning in query and mistake-bound models

Journal of Computer and System Sciences
Identification of partial disjunction, parity, and threshold functions

Theoretical Computer Science
Robust logics

Artificial Intelligence
Projection Learning

Machine Learning
A neuroidal architecture for cognitive computation

Journal of the ACM (JACM)
Concept Formation and Knowledge Revision

Concept Formation and Knowledge Revision
Theory Revision with Queries: DNF Formulas

Machine Learning
Queries and Concept Learning

Machine Learning
Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm

Machine Learning
Queries and Concept Learning

Machine Learning
Learning from Incomplete Boundary Queries Using Split Graphs and Hypergraphs

EuroCOLT '97 Proceedings of the Third European Conference on Computational Learning Theory
On Learning Disjunctions of Zero-One Treshold Functions with Queries

ALT '97 Proceedings of the 8th International Conference on Algorithmic Learning Theory
Theory revision with queries: horn, read-once, and parity formulas

Artificial Intelligence
Projective DNF formulae and their revision

Discrete Applied Mathematics
Bias-driven revision of logical domain theories

Journal of Artificial Intelligence Research

Quantified Score

Hi-index	5.23

Visualization

Abstract

We investigate regular tree languages' exact learning from positive examples and membership queries. Input data are trees of the language to infer. The learner computes new trees from the inputs and asks the oracle whether or not they belong to the language. ...