應(yīng)yl7703永利官網(wǎng)邀請，江西財(cái)經(jīng)大學(xué)統(tǒng)計(jì)學(xué)院江河博士將于2016年12月18日至12月20日訪問我校并作學(xué)術(shù)報(bào)告。

      報(bào)告題目：Group regularized estimation under structural hierarchy

      時(shí)      間：2016年12月19日（星期一）16：30
      地       點(diǎn)：齊云樓911報(bào)告廳

Abstract: In high-dimensional models that involve interactions, statisticians usually favor variable selection obeying certain logical hierarchical constraints. This paper focuses on structural hierarchy which means that the existence of an interaction term implies that at least one or both associated main effects must be present. Lately this problem has attracted a lot of attentions from statisticians, but existing computational algorithms converge slow and cannot meet the challenge of big data computation. More importantly, theoretical studies of hierarchical variable selection are extremely scarce, largely due to the difficulty that multiple sparsity-promoting penalties are enforced on the same subject. This work investigates a new type of estimator based on group multi-regularization to capture various types of structural parsimony simultaneously. We present non-asymptotic results based on combined statistical and computational analysis, and reveal the minimax optimal rate. A general-purpose algorithm is developed with a theoretical guarantee of strict iterate convergence and global optimality. Simulations and real data experiments demonstrate the efficiency and efficacy of the proposed approach.

       歡迎屆時(shí)參加。

江河博士簡介

       江河博士現(xiàn)就職于江西財(cái)經(jīng)大學(xué)統(tǒng)計(jì)學(xué)院，任助理教授。2005年9月至2009年6月就讀于yl7703永利官網(wǎng)數(shù)學(xué)基地班；2009年9月被保送至yl7703永利官網(wǎng)攻讀概率論與數(shù)理統(tǒng)計(jì)碩士學(xué)位; 2011年9月至2012年5月在美國奧本大學(xué)yl7703永利官網(wǎng)訪問學(xué)習(xí)；2012年9月至2015年5月于佛羅里達(dá)州立大學(xué)取得統(tǒng)計(jì)學(xué)博士學(xué)位。江河的研究領(lǐng)域?yàn)榇髷?shù)據(jù)下的變量選擇問題及其相關(guān)應(yīng)用。發(fā)表SCI學(xué)術(shù)8篇，主持江西省教育廳基金一項(xiàng)。

數(shù)學(xué)與復(fù)雜系統(tǒng)省級(jí)重點(diǎn)實(shí)驗(yàn)室

yl7703永利官網(wǎng)

萃英學(xué)院

2016年12月19日