• computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed...
    7 KB (907 words) - 02:44, 17 January 2025
  • theoretical viewpoint, probably approximately correct learning provides a framework for describing machine learning. The term machine learning was coined in 1959...
    140 KB (15,528 words) - 00:32, 8 August 2025
  • approaches include: Exact learning, proposed by Dana Angluin[citation needed]; Probably approximately correct learning (PAC learning), proposed by Leslie Valiant;...
    8 KB (865 words) - 00:46, 24 March 2025
  • Gold. Subsequently known as Algorithmic learning theory. Probably approximately correct learning (PAC learning) proposed in 1984 by Leslie Valiant Gold...
    2 KB (203 words) - 01:41, 16 November 2024
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    intractable. He created the Probably Approximately Correct or PAC model of learning that introduced the field of Computational Learning Theory and became a theoretical...
    14 KB (1,220 words) - 05:08, 28 May 2025
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    subspace learning Naive Bayes classifier Maximum entropy classifier Conditional random field Nearest neighbor algorithm Probably approximately correct learning...
    22 KB (3,049 words) - 23:34, 27 July 2025
  • in polynomial time. An example of such a framework is probably approximately correct learning [citation needed]. The concept was introduced in E. Mark...
    10 KB (1,149 words) - 02:49, 2 June 2025
  • algorithms that are provable boosting algorithms in the probably approximately correct learning formulation can accurately be called boosting algorithms...
    20 KB (2,178 words) - 15:45, 27 July 2025
  • generative models also began in the 1970s. A probably approximately correct learning bound for semi-supervised learning of a Gaussian mixture was demonstrated...
    22 KB (3,038 words) - 19:39, 8 July 2025
  • Hypothesis Theory (category Learning theory (education))
    knowledge (i.e., class) representability: Rough sets Probably approximately correct learning (PAC learning) Bold hypothesis Groner, Rudolf & Groner, Marina...
    3 KB (461 words) - 12:18, 2 December 2024
  • modeling Probably approximately correct learning (PAC) learning Ripple down rules, a knowledge acquisition methodology Symbolic machine learning algorithms...
    39 KB (3,385 words) - 07:36, 7 July 2025
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    properties, have important applications in machine learning, in the area of probably approximately correct learning. In computational geometry, they have been...
    17 KB (2,044 words) - 18:28, 28 February 2025
  • Kernel method Statistical learning theory Rademacher complexity Vapnik–Chervonenkis dimension Probably approximately correct learning Probability distribution...
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  • introduced Probably Approximately Correct Learning (PAC Learning), a framework for the mathematical analysis of machine learning. Symbolic machine learning encompassed...
    88 KB (11,042 words) - 18:53, 27 July 2025
  • . Machine learning Data mining Probably approximately correct learning Adversarial machine learning Valiant, L. G. (August 1985). Learning Disjunction...
    11 KB (1,904 words) - 04:07, 26 July 2025
  • Language identification in the limit (category Computational learning theory)
    of steps). A weaker formal model of learnability is the Probably approximately correct learning (PAC) model, introduced by Leslie Valiant in 1984. It is...
    21 KB (2,594 words) - 01:34, 28 May 2025
  • implementation of the online Q-learning algorithm, with probably approximately correct (PAC) learning. Greedy GQ is a variant of Q-learning to use in combination...
    30 KB (3,871 words) - 03:00, 8 August 2025
  • polynomial-time quantum algorithms which are correct WHP. Probably approximately correct learning: A process for machine-learning in which the learned function has...
    3 KB (406 words) - 04:59, 6 August 2025
  • received training data. This is closely related to probably approximately correct (PAC) learning, where the learner is evaluated on its predictive power...
    11 KB (1,710 words) - 02:07, 25 August 2023
  • Natarajan dimension (category Computational learning theory)
    In the theory of Probably Approximately Correct Machine Learning, the Natarajan dimension characterizes the complexity of learning a set of functions...
    2 KB (299 words) - 19:11, 26 June 2025
  • and they begin to babble later on in infancy—at approximately 11 months as compared to approximately 6 months for hearing babies. Prelinguistic language...
    112 KB (13,665 words) - 19:30, 6 August 2025
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    assumptions). A natural model of passive learning is Valiant's probably approximately correct (PAC) learning. Here the learner receives random examples...
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  • (XAI), often overlapping with interpretable AI or explainable machine learning (XML), is a field of research that explores methods that provide humans...
    71 KB (7,813 words) - 21:09, 27 July 2025
  • Large language model (category Deep learning)
    learning" allows AIs to "cheat" on multiple-choice tests by using statistical correlations in superficial test question wording to guess the correct responses...
    125 KB (13,357 words) - 09:43, 8 August 2025
  • OpenAI Codex (category Deep learning software applications)
    written without having to write as much code", and that "it is not always correct, but it is just close enough". According to a paper by OpenAI researchers...
    14 KB (1,379 words) - 19:13, 31 July 2025
  • between stability and consistency in ERM algorithms in the Probably Approximately Correct (PAC) setting. 2004 - Poggio et al. proved a general relationship...
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    languages, the correct use of prepositions in the English language is difficult to learn, and it can turn out to be quite a frustrating learning experience...
    110 KB (14,152 words) - 09:07, 15 July 2025
  • Concept class (category Computational learning theory)
    computational learning theory. Concept class terminology frequently appears in model theory associated with probably approximately correct (PAC) learning. In this...
    4 KB (537 words) - 18:13, 10 October 2023
  • probably approximately correct (PAC) model was applied by D. Roth (2002) to solve computer vision problem by developing a distribution-free learning theory...
    13 KB (2,001 words) - 13:37, 22 July 2025
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    responded correctly to sequences of novel stimuli that were arranged in the same order as those previously learned. Similar sequence learning has been...
    123 KB (15,112 words) - 10:12, 3 August 2025