Minimax analysis of active learning
WebThis paper aims to shed light on achievable limits in active learning. Using minimax analysis techniques, ... Dive into the research topics of 'Minimax bounds for active learning'. Together they form a unique fingerprint. Problem-Based Learning Engineering & Materials Science 100%. Learning ... 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 …
Minimax analysis of active learning
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Web19 nov. 2013 · In , the authors show that the minimax convergence rate for any active learning algorithm is bounded by n − κ 2 κ − 2, where n is the number of labeled instances and κ ≥ 1 is used in Tsybakov noise condition to characterize the behavior of Pr (Y = 1 X = x) in the neighborhood of the decision boundary. 1 1 1 We omit an additional parameter … WebMinimax Analysis of Active Learning Steve Hanneke, Liu Yang; 16 (109):3487−3602, 2015. Abstract This work establishes distribution-free upper and lower bounds on the …
Web3 okt. 2009 · Two novel BMAL techniques are proposed, which are a framework for dynamic batch mode active learning, which adaptively selects the batch size and the specific instances to be queried based on the complexity of the data stream being analyzed and a BMAL algorithm for fuzzy label classification problems. Expand PDF View 1 excerpt, … WebJournal of Machine Learning Research 16 (2015) 3487-3602 Submitted 10/14; Published 12/15 Minimax Analysis of Active Learning Steve Hanneke steve. sign in sign up. Minimax Analysis of Active Learning [PDF] Related documentation. Alpha-Beta Pruning; Game Theory with Translucent Players;
WebThis work establishes distribution-free upper and lower bounds on the minimax label complexity of active learning with general hypothesis classes, under various noise … WebThis work establishes distribution-free upper and lower bounds on the minimax label complexity of active learning with general hypothesis classes, under... Skip to main …
Web19 nov. 2013 · Active learning refers to the learning protocol where the learner is allowed to choose a subset of instances for labeling. Previous studies have shown that, compared with passive learning, active learning is able to reduce the label complexity exponentially if the data are linearly separable or satisfy the Tsybakov noise condition with parameter κ=1.
Web18 dec. 2024 · Minimax Active Learning. Sayna Ebrahimi, William Gan, Dian Chen, Giscard Biamby, Kamyar Salahi, Michael Laielli, Shizhan Zhu, Trevor Darrell. Active learning aims to develop label-efficient algorithms by querying the most representative samples to be labeled by a human annotator. Current active learning techniques either … right sided aortic arch symptoms in adultsWeb22 apr. 2008 · Active learning involves sequential sampling procedures that use information gleaned from previous samples in order to focus the sampling and accelerate the … right sided anatomical featuresWebpropose new active learning strategies that nearly achieve these minimax label complexities. Keywords: Active Learning, Selective Sampling, Sequential Design, Adaptive Sampling, Statisti- cal Learning Theory, Margin Condition, Tsybakov Noise, Sample … right sided abdo pain in womenWeb15 mei 2015 · We prove minimax lower and upper bounds which demonstrate that when σ is smaller than the minimiax active/passive noiseless error derived in CN07, then noise has no effect on the rates and one achieves the same noiseless rates. right sided antalgic gaitWeb3 okt. 2014 · In 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 … right sided abdominal pain and bloatingWebbakov (2004), the minimax label complexity of active learning with a VC class is always asymptotically smaller than that of passive learning, and is typically signi cantly … right sided anatomical features imageWebThis 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 number of surprising facts. In particular, under the noise model of Tsybakov (2004), the minimax label complexity of active learning with a VC class is … right sided arch radiology