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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… 
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Related topics

Related topics

20 relations
ACM Turing AwardAlgorithmic learning theoryComputational complexity theoryConcept class

Broader (1)

Computational learning theory

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Probably Approximately Correct Learning of Regulatory Networks from Time-Series Data
Automating the process of model building from experimental data is a very desirable goal to palliate the lack of modellers for… 
2017
2017
Probably Approximately Correct Learning
  • Stan Hatko
  • Encyclopedia of Machine Learning and Data Mining
  • 2017
  • Corpus ID: 29030328
2015
2015
An approach to one-bit compressed sensing based on probably approximately correct learning theory
This paper builds upon earlier work of the authors in formulating the one-bit compressed sensing (OBCS) problem as a problem in… 
Highly Cited
2012
Highly Cited
2012
Diversity Regularized Ensemble Pruning
Diversity among individual classifiers is recognized to play a key role in ensemble, however, few theoretical properties are… 
2004
2004
Probably Approximately Correct Learning with Beta-Mixing Input Sequences
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… 
1995
1995
Probably approximately correct learning in fuzzy classification systems
An efficient method for learning (trapezoidal) membership functions for fuzzy predicates is presented. Positive and negative… 
Highly Cited
1995
Highly Cited
1995
Theory and Applications of Agnostic PAC-Learning with Small Decision Trees
1994
1994
Refutably Probably Approximately Correct Learning
We propose a notion of the refutably PAC learning, which formalizes the refutability of hypothesis spaces in the PAC learning… 
Review
1993
Review
1993
The Probably Approximately Correct (PAC) and Other Learning Models
This paper surveys some recent theoretical results on the efficiency of machine learning algorithms. The main tool described is… 
Highly Cited
1992
Highly Cited
1992
PAC-learnability of determinate logic programs
The field of Inductive Logic Programming (ILP) is concerned with inducing logic programs from examples in the presence of… 
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