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СЕМИНАРЫ |
Городской семинар по теории вероятностей и математической статистике
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Statistical Inference With High-Dimensional Data Cun-Hui Zhang, |
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Аннотация: We consider statistical inference in a semi-low-dimensional approach to the analysis of high-dimensional data. The relationship between this semi-low-dimensional approach and regularized estimation of high-dimensional objects is parallel to the more familiar one between semiparametric analysis and nonparametric estimation. Low-dimensional projection methods are used to correct the bias of regularized high-dimensional estimators, leading to efficient point and interval estimation. Bootstrap can be used to carry out simultaneous inference. Only a small fraction of labelled data are needed in a semisupervised setting. Examples include regression and graphical models for continuous and binary data. Язык доклада: английский |