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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems

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  • TA的每日心情
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    2016-3-19 06:18
  • 签到天数: 18 天

    [LV.4]偶尔看看III

    发表于 2015-9-24 09:30:27 | 显示全部楼层 |阅读模式
    Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: école d'été de Probabilités de, 2011
    by Vladimir Koltchinskii PDF
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    The purpose of these lecture notes is to provide an introduction to the general theory of empirical risk minimization with an emphasis on excess risk bounds and oracle inequalities in penalized problems. In recent years, there have been new developments in this area motivated by the study of new classes of methods in machine learning such as large margin classification methods (boosting, kernel machines). The main probabilistic tools involved in the analysis of these problems are concentration and deviation inequalities by Talagrand along with other methods of empirical processes theory (symmetrization inequalities, contraction inequality for Rademacher sums, entropy and generic chaining bounds). Sparse recovery based on l_1-type penalization and low rank matrix recovery based on the nuclear norm penalization are other active areas of research, where the main problems can be stated in the framework of penalized empirical risk minimization, and concentration inequalities and empirical processes tools have proved to be very useful.
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  • TA的每日心情
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    2017-12-15 11:07
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    [LV.7]常住居民III

    发表于 2016-2-13 13:55:04 | 显示全部楼层
    谢谢楼主辛苦分享!!
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    发表于 2017-12-17 02:30:23 | 显示全部楼层
    thanks very much
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  • TA的每日心情
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    2019-10-19 22:31
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    [LV.1]初来乍到

    发表于 2019-10-19 21:56:53 | 显示全部楼层
    经验风险最小和稀疏复原问题Oracle不等式
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