<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div class=""><span class="" style="font-size: 14px; orphans: 2; widows: 2;">UNIVERSITY OF CHICAGO</span><br class="" style="font-size: 14px; orphans: 2; widows: 2;"><span class="" style="font-size: 14px; orphans: 2; widows: 2;">DEPARTMENT OF COMPUTER SCIENCE</span></div><div class="" style="orphans: 2; widows: 2;"><span class="" style="font-size: 14px;">PRESENTS</span></div><div class="" style="orphans: 2; widows: 2;"><span class="" style="font-size: 14px;"><br class=""></span></div><div class="" style="orphans: 2; widows: 2;"><span class="" style="font-size: 12pt; font-family: Helvetica, sans-serif;"><img apple-inline="yes" id="A9B088CB-047E-4C95-90D4-2DEF14A7083A" height="107" width="70" apple-width="yes" apple-height="yes" src="cid:clip_image002.png" class=""></span> </div><div class="" style="orphans: 2; widows: 2;"><br class=""></div><div class="" style="orphans: 2; widows: 2;"><div class="" style="margin: 0in 0in 0.0001pt;"><span class="" style="font-size: 14px;"><b class="">Jiantao Jiao</b></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class="" style="font-size: 14px;"><b class="">Stanford University</b></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><br class=""></div><div class="" style="margin: 0in 0in 0.0001pt;"><b class=""><font class="" style="font-size: 14px;"><br class=""></font></b></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class="" style="font-size: 14px;"><b class=""><font class="">Monday, February 5, 2018 at 2:30 pm <br class="">Ryerson 251</font></b><br class=""></span></div></div><div class="" style="orphans: 2; widows: 2;"><span class="" style="font-size: 14px;"><br class=""></span></div><div class=""><br class=""></div><div class=""><div class=""><b class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">Title: </b><font color="#212121" face="Roboto, Helvetica, Arial, sans-serif" class=""><span class="" style="font-size: 14px;">Statistical inference of properties of distributions: theory, algorithms, and applications </span></font></div><div class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"><b class=""><br class=""></b></div><div class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"><b class="">Abstract:</b></div><div class=""><font color="#212121" face="Roboto, Helvetica, Arial, sans-serif" class=""><span class="" style="font-size: 14px;">Modern data science applications—ranging from graphical model learning to image registration to inference of gene regulatory networks—frequently involve pipelines of exploratory analysis requiring accurate inference of a property of the distribution governing the data rather than the distribution itself. Notable examples of properties include Shannon entropy, mutual information, Kullback-Leibler divergence, and total variation distance, among others. <br class=""><br class="">This talk will focus on recent progress in the performance, structure, and deployment of near-minimax-optimal estimators for a large variety of properties in high-dimensional and nonparametric settings. We present general methods for constructing information theoretically near-optimal estimators, and identify the corresponding limits in terms of the parameter dimension, the mixing rate (for processes with memory), and smoothness of the underlying density (in the nonparametric setting). We employ our schemes on the Google 1 Billion Word Dataset to estimate the fundamental limit of perplexity in language modeling, and to improve graphical model and classification tree learning. The estimators are efficiently computable and exhibit a "sample size boosting” phenomenon, i.e., they attain with n samples what prior methods would have needed n log(n) samples to achieve. <br class=""><br class=""></span></font><b class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">Bio:</b></div><div class=""><i class=""><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">Jiantao Jiao is a Ph.D. student in the Department of Electrical Engineering at Stanford University. He received the B.Eng. degree in Electronic Engineering from Tsinghua University,</span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"> </span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">Beijing, China in 2012, and the M.Eng. degree in Electrical Engineering from Stanford University in 2014. He is a recipient of the Presidential Award of Tsinghua University and the Stanford</span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"> </span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">Graduate Fellowship. He was a semi-plenary speaker at ISIT 2015 and a co-recipient of the ISITA 2016 Student Paper Award. He co-designed and co-taught the graduate course EE378A</span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"> </span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">(Statistical Signal Processing) at Stanford University in 2016 and 2017, with his advisor Tsachy Weissman. His research interests are in statistical machine learning, high-dimensional and</span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"> </span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">nonparametric statistics, information theory, and their applications in medical imaging, genomics, and natural language processing. He is a co-founder of Qingfan (</span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"><a href="http://www.qingfan.com" class="">www.qingfan.com</a></span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;">), an</span><span class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"> online platform that democratizes technical training and job opportunities for anyone with access to the internet.</span></i></div><div class=""><i class="" style="color: rgb(33, 33, 33);"><br class=""></i></div><div class=""><div class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"><b class="">Host: Risi Kondor</b></div><div class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14px;"><br class=""></div><div class="" style="color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif;"><i class=""><font size="2" class="">Refreshments served after the talk in Ry. 255</font></i></div></div></div></body></html>