We propose an algorithm called query by committee, in which a committee of students is trained on the same data set. The next query is chosen according to the principle of maximal...
H. Sebastian Seung, Manfred Opper, Haim Sompolinsk...
In this paper we initiatean investigationof generalizationsof the ProbablyApproximatelyCorrect (PAC) learningmodelthat attemptto significantlyweakenthe target functionassumptions.T...
Michael J. Kearns, Robert E. Schapire, Linda Selli...
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Machine learning of limit programs (i.e., programs allowed finitely many mind changes about their legitimate outputs) for computable functions is studied. Learning of iterated lim...
We consider learning in situations where the function used to classify examples may switch back and forth between a small number of different concepts during the course of learnin...
This paper deals with a class of Prolog programs, called context-free term transformations (CFT). We present a polynomial time algorithm to identify a subclass of CFT, whose progr...
We consider PAC-learning where the distribution is known to the student. The problem addressed here is characterizing when learnability with respect to distribution D1 implies lea...