jmlr jmlr2012 jmlr2012-91 jmlr2012-91-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Stanislav Minsker
Abstract: We present a new active learning algorithm based on nonparametric estimators of the regression function. Our investigation provides probabilistic bounds for the rates of convergence of the generalization error achievable by proposed method over a broad class of underlying distributions. We also prove minimax lower bounds which show that the obtained rates are almost tight. Keywords: active learning, selective sampling, model selection, classification, confidence bands
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