<html><head><meta http-equiv="Content-Type" content="text/html; charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div dir="auto" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div dir="auto" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div dir="auto" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; 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-webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div class=""><span class="" style="orphans: 2; widows: 2; font-size: large;">UNIVERSITY OF CHICAGO</span></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div class=""><span class=""><font size="4" class="">DEPARTMENT OF COMPUTER SCIENCE</font></span></div><div class="" style="orphans: 2; widows: 2;"><span class=""><font size="4" class="">PRESENTS</font></span></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><div class=""><br class="webkit-block-placeholder"></div><p class="MsoNormal"><o:p class=""> </o:p><img apple-inline="yes" id="10545F62-F0EC-481B-A70B-37766662D53E" src="cid:1D7F0EC4-61C5-4F60-8FE2-50F0B936E5B4@hsd1.il.comcast.net" class=""></p><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div class="" style="orphans: 2; widows: 2;"><font size="4" class=""><b class="">Anqi (Angie) Liu</b></font></div><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" class="" style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div class="" style="orphans: 2; widows: 2;"><div class="" style="margin: 0in 0in 0.0001pt;"><font size="4" class=""><i class="">California Institute of Technology</i></font></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class="" style="font-size: 14px;"><i class=""><p class="MsoNormal" align="center"><o:p class=""></o:p></p></i></span><div class=""><br class=""></div></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class=""><span class=""><font class=""><font size="4" class=""><b class="">Wednesday, February 10th at 3:00 pm</b></font></font></span></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class=""><br class=""></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class=""><span class="" style="font-size: 15px;">Join via zoom (enables questions):</span></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class="" style="font-size: 15px;"><a href="https://uchicago.zoom.us/j/93538066915?pwd=aXlxS2tpbnRnSUI1RndCbHZLYUVBUT09" class="">https://uchicago.zoom.us/j/93538066915?pwd=aXlxS2tpbnRnSUI1RndCbHZLYUVBUT09</a><br class="">Passcode: uccs2021<span class=""><br class=""> </span></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class=""><span class="" style="font-size: 15px;">Or</span></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><span class=""><span class="" style="font-size: 15px;"><br class="">Watch via live stream:<br class=""></span></span></div><div class="" style="margin: 0in 0in 0.0001pt;"><a href="http://live.cs.uchicago.edu/anqiliu/" style="font-size: 15px;" class="">http://live.cs.uchicago.edu/anqiliu/</a></div></div><div class=""><div class=""><font size="4" class=""><font class=""><span class=""><b class="" style="color: rgb(33, 33, 33);"><br class=""></b></span></font></font></div><div class=""><span class="" style="font-size: 15px;"><font class=""><font class=""><span class=""><b class="" style="color: rgb(33, 33, 33);">Title: </b></span></font></font><font color="#212121" class=""><span class=""><b class="">Towards Trustworthy AI: Provably Robust Extrapolation for Decision Making</b></span></font></span></div><div class=""><font color="#212121" class=""><span class="" style="font-size: 15px;"><b class=""><br class=""></b></span></font></div><div class=""><span class="" style="color: rgb(33, 33, 33); font-size: 15px;"><b class=""><font class="">Abstract: </font></b></span><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap; color: rgb(33, 33, 33);" class="">To create trustworthy AI systems, we must safeguard machine learning methods from catastrophic failures. For example, we must account for the uncertainty and guarantee the performance for</span><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap; color: rgb(33, 33, 33);" class=""> </span><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap; color: rgb(33, 33, 33);" class="">safety-critical systems, like in autonomous driving and health care, before deploying them in the real world. A key challenge in such real-world applications is that the test cases are not well</span><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap; color: rgb(33, 33, 33);" class=""> </span><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap; color: rgb(33, 33, 33);" class="">represented by the pre-collected training data. To properly leverage learning in such domains, we must go beyond the conventional learning paradigm of maximizing average prediction accuracy</span><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap; color: rgb(33, 33, 33);" class=""> </span><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap; color: rgb(33, 33, 33);" class="">with generalization guarantees that rely on strong distributional relationships between training and test examples.</span></div><font color="#212121" class=""><span style="caret-color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""><br class="">In this talk, I will describe a distributionally robust learning framework that offers accurate uncertainty quantification and rigorous guarantees under data distribution shift. This framework yields appropriately conservative yet still accurate predictions to guide real-world decision-making and is easily integrated with modern deep learning. I will showcase the practicality of this framework in applications on agile robotic control and computer vision. I will also introduce a survey of other real-world applications that would benefit from this framework for the future work.<br class=""><br class=""></span></font><div class=""><font class=""><span class=""><div class="" style="font-variant-ligatures: normal; background-color: rgb(255, 255, 255);"><div class=""><font class=""><b class="" style="font-size: 15px; color: rgb(33, 33, 33);">Bio: </b></font><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class="">Anqi (Angie) Liu is a postdoctoral scholar research associate at the Department of Computing and Mathematical Sciences in the California Institute of Technology. She obtained her Ph.D. from the</span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""> </span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class="">Department of Computer Science of the University of Illinois at Chicago. She is interested in machine learning for safety-critical tasks and the societal impact of AI. She aims to design principled</span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""> </span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class="">learning methods and collaborate with domain experts to build more reliable systems for the real world.</span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""> </span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class="">She currently works on distributionally robust learning, distribution shift, and interactive</span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""> </span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class="">machine learning.</span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""> </span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class="">She has been selected for the EECS Rising Star in UC Berkeley 2020. Her publication appears in prestigious machine learning conferences like Neurips, ICML, ICLR, AAAI, and</span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""> </span><span style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class="">AISTAT.</span></div><br style="caret-color: rgb(33, 33, 33); color: rgb(33, 33, 33); font-size: 15px; white-space: pre-wrap;" class=""></div></span></font></div><div class=""><div class="" style="font-variant-ligatures: normal; background-color: rgb(255, 255, 255);"><font color="#222222" class=""><i class=""><b class=""><font class="" style="font-size: 15px;">Host: Yuxin Chen</font></b></i></font></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></body></html>