WebAug 12, 2014 · Download PDF Abstract: We prove new fast learning rates for the one-vs-all multiclass plug-in classifiers trained either from exponentially strongly mixing data or from data generated by a converging drifting distribution. These are two typical scenarios where training data are not iid. The learning rates are obtained under a multiclass … WebFast learning rates for plug-in classifiers - Laboratoire de ...
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WebJul 8, 2005 · Fast learning rates for plug-in classifiers under the margin condition. It has been recently shown that, under the margin (or low noise) assumption, there exist classiflers attaining fast rates of convergence of the excess Bayes risk, i.e., the rates faster than n i1=2 . The works on this subject suggested the following two conjectures: (i) the ... WebFast learning rates for plug-in classifiers The Annals of Statistics You are using an outdated, unsupported browser. Upgrade to a modern browser such as Chrome , … top gmc vehicles
[PDF] Learning From Non-iid Data: Fast Rates for the One-vs-All ...
WebFast learning rates for plug-in classifiers. The Annals of Statistics, 35(2):608-633, 2007. Google Scholar Cross Ref; M.-F. Balcan and S. Hanneke. Robust interactive learning. ... Learning nested differences of intersection-closed concept classes. Machine Learning, 5:165-196, 1990. Google Scholar Digital Library; WebOct 1, 2024 · The fast learning rate for sub-gaussian and sub-exponential losses are done in the context of density estimation , and for general losses , of which ... Fast learning rates for plug-in classifiers. Ann. Stat., 35 (2) (2007), pp. 608-633. View Record in Scopus Google Scholar. WebAug 17, 2007 · Title: Fast learning rates for plug-in classifiers. ... {-1}$, and (ii) the plug-in classifiers generally converge more slowly than the classifiers based on empirical risk … picture of usa flag