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Probably approximately correct learning

Known as: Probably approximately correct, PAC-learning, PAC Learning 
In computational learning theory, probably approximately correct learning (PAC learning) is a framework for mathematical analysis of machine learning… Expand
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Papers overview

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2016
2016
We consider a controller synthesis problem in turn-based stochastic games with both a qualitative linear temporal logic (LTL… Expand
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Highly Cited
2014
Highly Cited
2014
We consider synthesis of control policies that maximize the probability of satisfying given temporal logic specifications in… Expand
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Highly Cited
2014
Highly Cited
2014
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this… Expand
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2004
2004
In this paper, we study the behaviour of PAC learning algorithms when the input sequence is not i.i.d., but is β-mixing instead… Expand
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1995
1995
An efficient method for learning (trapezoidal) membership functions for fuzzy predicates is presented. Positive and negative… Expand
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1994
1994
We propose a notion of the refutably PAC learning, which formalizes the refutability of hypothesis spaces in the PAC learning… Expand
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Highly Cited
1994
Highly Cited
1994
The probably approximately correct learning model Occam's razor the Vapnik-Chervonenkis dimension weak and strong learning… Expand
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Highly Cited
1991
Highly Cited
1991
In many domains, an appropriate inductive bias is the MIN-FEATURES bias, which prefers consistent hypotheses definable over as… Expand
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Review
1990
Review
1990
  • David Haussler
  • Encyclopedia of Machine Learning and Data Mining
  • 1990
  • Corpus ID: 1797236
This paper surveys some recent theoretical results on the efficiency of machine learning algorithms. The main tool described is… Expand
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Highly Cited
1988
Highly Cited
1988
We consider the problem of using queries to learn an unknown concept. Several types of queries are described and studied… Expand
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