Minimax bounds for active learning
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Minimax bounds for active learning
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WebIEEE Transactions on Information Theory. Periodical Home; Latest Issue; Archive; Authors; Affiliations; Home Browse by Title Periodicals IEEE Transactions on Information Theory Vol. 54, No. 5 Minimax Bounds for Active Learning Browse by Title Periodicals IEEE Transactions on Information Theory Vol. 54, No. 5 Minimax Bounds for Active Learning WebMinimax Regret Bounds for Reinforcement Learning and belongs to the interval [0;1].3 In this paper we focus on the setting where the reward func-tion Ris known, but extending our algorithm to unknown stochastic rewards poses no real difficulty. The policy during an episode is expressed as a mapping ˇ : S [H] !A. The value Vˇ h: S !R de-
WebThis article is partially a review and partially a contribution. The classical two approaches to robustness, Huber’s minimax and Hampel’s based on influence functions, are reviewed with the accent on distribution classes of a non-neighborhood nature. Mainly, attention is paid to the minimax Huber’s M-estimates of location designed for the classes with bounded … Web29 apr. 2010 · We describe and explore a new perspective on the sample complexity of active learning. In many situations where it was generally believed that active learning …
WebPaper Minimax analysis of active learning Abstract This work establishes distribution-free upper and lower bounds on the minimax label complexity of active learning with general hypothesis classes, under various noise models. The results reveal a … WebMinimax Bounds for Active Learning Rui M. Castro 1,2 and Robert D. Nowak 1 University of Wisconsin, Madison WI 53706, USA, [email protected],[email protected], 2 …
http://proceedings.mlr.press/v70/azar17a/azar17a.pdf
Web29 apr. 2010 · This work establishes distribution-free upper and lower bounds on the minimax label complexity of active learning with general hypothesis classes, under … pull down shade screenWebMinimax bounds on stochastic batched convex optimization. In Conference On Learning Theory, pages 3065–3162, 2024. [EDMM06] Eyal Even-Dar, Shie Mannor, and Yishay Mansour. Action elimination and stopping conditions for the multi-armed bandit and reinforcement learning problems. Journal of machine learning research, … pull down sink faucetsWebIn particular, under the noise model of Tsybakov (2004), the minimax label complexity of active learning with a VC class is always asymptotically smaller than that of passive … pull down shop storage drawer slidesWebActive learning involves sequential sampling procedures that use information gleaned from pr... Minimax Bounds for Active Learning IEEE Transactions on Information Theory … seattle to lax cheap flightsWebThis paper aims to shed light on achievable limits in active learning. Using minimax analysis techniques, we study the achievable rates of classification error convergence for … pull down shutter doorWeb13 jun. 2007 · In [11], the authors show that the minimax convergence rate for any active learning algorithm is bounded by n − κ 2κ−2 , where n is the number of labeled … seattle to las vegas round tripWeb1 jan. 2008 · Our results indicate that humans are capable of actively selecting informative queries, and in doing so learn better and faster than if they are given random training data, as predicted by... seattle to la west coast train tours