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jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.295ca3fee9ceab89_63" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe lkHyyc"><h1 id="h.h03t1bnbjczv" dir="ltr" class="CDt4Ke zfr3Q duRjpb" style="text-align: center;">Live plenary talks</h1></div></div></div></div></div></div></div></div></div></section><section id="h.f3658277815dfb2_7" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.f3658277815dfb2_4" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q">All live plenary talks will be given twice to allow everyone in the world to attend the live talks without getting up in the middle of the night. The talks will be held in the <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms">"Conference hall" zoom room</a></span> and additionally stremed live on YouTube.</p></div></div></div></div></div></div></div></div></div></section><section id="h.1b2ba4ccc63ba5cd_0" class="yaqOZd qeLZfd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.1b2ba4ccc63ba5cd_3" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="text-align: center;"><span style="font-family: Lato;"><strong>Only </strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/registration"><strong>registered participants</strong></a></span><span style="font-family: Lato;"><strong> will receive the password to the zoom rooms by email.</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.429aae233c85530e_4" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.429aae233c85530e_7" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><div id="h.ad63jmw7s98y" class="CobnVe aP9Z7e"></div><h2 id="h.ad63jmw7s98y_l" dir="ltr" class="CDt4Ke zfr3Q JYVBee" tabindex="-1"><div jscontroller="Ae65rd" jsaction="touchstart:UrsOsc; click:KjsqPd; focusout:QZoaZ; mouseover:y0pDld; mouseout:dq0hvd;fv1Rjc:jbFSOd;CrfLRd:SzACGe;" class="CjVfdc"><div class="PPhIP rviiZ" jsname="haAclf"><div role="presentation" class="U26fgb mUbCce fKz7Od LRAOtb Znu9nd M9Bg4d" jscontroller="mxS5xe" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-describedby="h.ad63jmw7s98y_l" aria-label="Copy heading link" aria-disabled="false" data-tooltip="Copy heading link" aria-hidden="true" data-tooltip-position="top" data-tooltip-vertical-offset="12" data-tooltip-horizontal-offset="0"><a class="FKF6mc TpQm9d" href="#h.ad63jmw7s98y" aria-label="Copy heading link" jsname="hiK3ld" role="button" aria-describedby="h.ad63jmw7s98y_l"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -11px"><svg class="OUGEr QdAdhf" width="22px" height="22px" viewBox="0 0 24 24" fill="currentColor" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"/></svg></span></span></a></div></div>Plenary speakers</div></h2></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_11" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_6" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;">E<span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">mmanuel Candes (Stanford): Conformal prediction in 2020</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_8" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://youtu.be/61tpigfLHso" target="_blank">Video can be found here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Abstract: Recent progress in machine learning provides us with many potentially effective tools to learn from datasets of ever-increasing sizes and make useful predictions. How do we know that these tools can be trusted in critical and highly-sensitive domains? If a learning algorithm predicts the GPA of a prospective college applicant, what guarantees do we have concerning the accuracy of this prediction? How do we know that it is not biased against certain groups of applicants? To address questions of this kind, this talk reviews a wonderful field of research known under the name of conformal inference/prediction, pioneered by Vladimir Vovk and his colleagues 20 years ago. After reviewing some of the basic ideas underlying distribution-free predictive inference, we shall survey recent progress in the field touching upon several issues: (1) efficiency: how can we provide tighter predictions?, (2) data-reuse: what do we do when data is scarce? (3) algorithmic fairness: how do we make sure that learned models apply to individuals in an equitable manner?, and (4) causal inference: can we predict the counterfactual response to a treatment given that the patient was not treated?</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato;"><strong>Thursday</strong></span><span style="font-family: Lato; font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"><strong>, August 2</strong></span><span style="font-family: Lato;"><strong>7</strong></span><span style="font-family: Lato; font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"><strong>th, </strong></span><span style="font-family: Lato;"><strong>0am </strong></span><span style="font-family: Lato; font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"><strong>and</strong></span><span style="font-family: Lato;"><strong> 3pm UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_12" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_15" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;">Martin Hairer (London): <span style="font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;">Stochastic Yang-Mills</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_17" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2F23z41alw3ycrmmz%2Fslides_Bernoulli.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw3c9LSYgM6J-Y5ymHitaIGZ" target="_blank">Slides can be found here</a></span>, <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://youtu.be/J7ErRth0lWE" target="_blank">video here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q">Abstract: <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Quantum gauge theories are the most successful models for the description of nature at its fundamental level. Unfortunately, despite decades of intense effort, their mathematical foundations remain murky. In this lecture, I will present recent results yielding some first steps towards the construction of quantum Yang-Mills theories in space-time dimensions 2 and 3. I will focus on the probabilistic aspects, so no prior knowledge of QFT is required. This is joint work with A. Chandra, I. Chevyrev and H. Shen.</span></p><p dir="ltr" class="CDt4Ke zfr3Q"><span style="font-family: Lato;"><strong>Monday, August 24th, 8am and 4pm in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_18" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_21" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Kerrie Mengers</span>e<span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">n (Queensland): </span>Modelling and Analysis of Crowdsourced Data </p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_23" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2F2cmpqicyhpj5a7a%2FIMS_Bernoulli_Presentation_0820.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw1g49KijLza0tLmJ74JuKB7" target="_blank">Slides can be found here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;">Abstract: So-called ‘citizen science’ is increasingly being employed for scientific endeavours and as a new data source. In this presentation I will describe some of our early efforts to utilise these data for statistical modelling. I will focus on three case studies: a more traditional example of using data obtained from local citizens, a more modern challenge of using data obtained from crowds and a slightly different example of using data from wearable sensors. In the first study, the derived stochastic model facilitates evaluation of the impact of various scenarios of climate change. In the second study, the Bayesian statistical models account for the proficiency of the citizens and the difficulty of the tasks in order to produce relevant ecological measures. The last study focuses on obtaining and understanding the intrinsic dimension of team sport. This work was undertaken with a range of collaborators who will be acknowledged in the presentation.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span style="font-family: Lato;"><strong>Monday, August 24th, 9pm in UTC and Tuesday, August 25th, 7am in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_24" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_27" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Wendelin Werner (Zurich):</span> <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">How to derive the values of some "divide-and-color" exponents</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_29" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.youtube.com/watch?v=Y8C2xjTlBEk&list=PLidqLPRgLpiMZBmdgCfa3L4MeQoOnPjFf&index=9&t=0s" target="_blank">Video can be found here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;">Abstract: <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Consider critical percolation, or a critical FK-percolation model in a half-plane. Color each cluster in green or blue independently with probability p or 1-p. How do we expect the probability that a given boundary point is in a green cluster of radius at least R to decay as R goes to infinity? </span> <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">We will try to describe some of the many ingredients that go into the determination of those critical exponents. This includes SLE paths and their generalizations, Conformal loop ensembles, Liouville Quantum Gravity ideas and features of stable growth-fragmentation trees. This is based on joint work with Jason Miller and Scott Sheffield.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato;"><strong>Friday, August 28th, 8am in UTC and 3pm in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.429aae233c85530e_0" class="yaqOZd qeLZfd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.429aae233c85530e_3" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><div id="h.6phzq3185rxg" class="GV3q8e aP9Z7e"></div><h3 id="h.6phzq3185rxg_l" dir="ltr" class="CDt4Ke zfr3Q OmQG5e" tabindex="-1"><div jscontroller="Ae65rd" jsaction="touchstart:UrsOsc; click:KjsqPd; focusout:QZoaZ; mouseover:y0pDld; mouseout:dq0hvd;fv1Rjc:jbFSOd;CrfLRd:SzACGe;" class="CjVfdc"><div class="PPhIP rviiZ" jsname="haAclf"><div role="presentation" class="U26fgb mUbCce fKz7Od LRAOtb Znu9nd M9Bg4d" jscontroller="mxS5xe" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-describedby="h.6phzq3185rxg_l" aria-label="Copy heading link" aria-disabled="false" data-tooltip="Copy heading link" aria-hidden="true" data-tooltip-position="top" data-tooltip-vertical-offset="12" data-tooltip-horizontal-offset="0"><a class="FKF6mc TpQm9d" href="#h.6phzq3185rxg" aria-label="Copy heading link" jsname="hiK3ld" role="button" aria-describedby="h.6phzq3185rxg_l"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -11px"><svg class="OUGEr QdAdhf" width="22px" height="22px" viewBox="0 0 24 24" fill="currentColor" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"/></svg></span></span></a></div></div><span class=" OGiC0d" style="font-style: normal; text-decoration: normal; vertical-align: baseline;">Bernoulli Society New Researcher Award</span></div></h3></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_49" class="yaqOZd qeLZfd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_44" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Nina Holden (Zurich): Liouville random surfaces and their central charge</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_46" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2Fup5tvfe9dhku34u%2Fc-greater-than-1-ows.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw1jfBMH6QvcmPHZaBmbd9Qe" target="_blank">Slides can be found here</a></span>, <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.youtube.com/watch?v=v5VbifVPBaE&list=PLidqLPRgLpiMZBmdgCfa3L4MeQoOnPjFf&index=11&t=0s" target="_blank">video here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Abstract: Liouville quantum gravity (LQG) is a theory of random fractal surfaces with origin in the physics literature in the 1980s. Most literature is about LQG with matter central charge ${\mathbf c}\in(-\infty,1]$. We first review theory of LQG and then we study a discretization of LQG which makes sense for all ${\mathbf c} \in (-\infty,25)$. Based on a joint work with Gwynne, Pfeffer, and Remy. </span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"><strong>Monday, </strong></span><span style="font-family: Lato;"><strong>August 24th, 9am and 3pm both in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_50" class="yaqOZd qeLZfd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_53" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Xin Sun (Pennsylvania): Quantum Liouville theory on the torus</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_55" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2Fpigwk1ipna9rcc5%2FSlides_Sun.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw1kjAOqy8r7_km0IGEYbaI8" target="_blank">Slides can be found here</a></span>, <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://youtu.be/JGOYkTBw49U" target="_blank">video here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Abstract: Quantum Liouville theory is a locally trivial but globally nontrivial perturbation of the Gaussian free field on 2D Riemannian manifolds. Its importance lies in two aspects. First, it governs the random conformal geometry that describes the 2D quantum gravity. Second, it is a primary example of conformal field theory. In this talk we review both aspects of the subject from a probabilistic point of view, with an emphasis on the torus. A joint work with P. Ghosal, G. Remy, and Y. Sun will be featured, and several open questions will be presented.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato;"><strong>Thursday, August 27th, 1am and 4pm UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_56" class="yaqOZd qeLZfd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_59" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-indent: 0;">Li-Cheng Tsai (Rutgers): <span style="font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;">Tails and moments of stochastic PDEs</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_61" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2Fgi18z40xm6cazhb%2Ftails.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw1jCk5VlJLbZ7PQFjDoMjLq" target="_blank">Slides can be found here</a></span>, <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://youtu.be/y-94fEUTw4k" target="_blank">video here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;">Abstract: <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">This talk focuses on two aspects of stochastic PDEs: large deviations and moments. I will present recent results on the one-point large deviations of the KPZ equation, and explain how moments of the stochastic heat equation plays a role in obtaining these tail probabilities.</span> <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Part of the talk will be based on joint work with Sayan Das and joint work with Yu Gu and Jeremy Quastel</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"><strong>Tuesday, August 25</strong></span><span style="font-family: Lato;"><strong>th, 11pm in UTC and Wednesday, August 26th, 2pm in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_40" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.76e1d8ac831fa0a1_43" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><div id="h.uq9mghlt1n36" class="GV3q8e aP9Z7e"></div><h3 id="h.uq9mghlt1n36_l" dir="ltr" class="CDt4Ke zfr3Q OmQG5e" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;" tabindex="-1"><div jscontroller="Ae65rd" jsaction="touchstart:UrsOsc; click:KjsqPd; focusout:QZoaZ; mouseover:y0pDld; mouseout:dq0hvd;fv1Rjc:jbFSOd;CrfLRd:SzACGe;" class="CjVfdc"><div class="PPhIP rviiZ" jsname="haAclf"><div role="presentation" class="U26fgb mUbCce fKz7Od LRAOtb Znu9nd M9Bg4d" jscontroller="mxS5xe" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-describedby="h.uq9mghlt1n36_l" aria-label="Copy heading link" aria-disabled="false" data-tooltip="Copy heading link" aria-hidden="true" data-tooltip-position="top" data-tooltip-vertical-offset="12" data-tooltip-horizontal-offset="0"><a class="FKF6mc TpQm9d" href="#h.uq9mghlt1n36" aria-label="Copy heading link" jsname="hiK3ld" role="button" aria-describedby="h.uq9mghlt1n36_l"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -11px"><svg class="OUGEr QdAdhf" width="22px" height="22px" viewBox="0 0 24 24" fill="currentColor" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"/></svg></span></span></a></div></div><span class=" OGiC0d" style="font-family: Lato; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fimstat.org%2Fims-awards%2Fims-lawrence-d-brown-ph-d-student-award%2F&sa=D&sntz=1&usg=AOvVaw1Vq6rIpn_lqhWKkyuSwO9k" target="_blank">IMS Lawrence D. Brown Ph.D. Student Award</a></span></div></h3></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_67" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_62" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Yuqi Gu (Michigan):</span><span style="font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"> Identification and Estimation of Structured and Hierarchical Latent Attribute Models</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_64" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2Fu716g9s14l5wtao%2FYuqiGu_slides_Aug20.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw2cbitjiIC-ZZ0zlt8xrNXi" target="_blank">Slides can be found here</a></span>, <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://youtu.be/Sq94qegjYb8" target="_blank">video here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;">Abstract: Hierarchical latent attribute models are a type of discrete latent variable models that have been attracting increasing attention in educational, psychological, and behavioral sciences. The key ingredients of such models include a binary structural matrix and a directed acyclic graph specifying hierarchical constraints on the configurations of latent attributes. These ingredients encode practitioners’ design information and carry important scientific meanings. In exploratory latent attribute analysis, it is of great practical interest to develop methods to estimate the significant latent attribute patterns and the attribute hierarchy graph. More fundamentally, it is an important yet open theoretical question of whether and when the structural matrix and the attribute hierarchy are uniquely identifiable. In this talk, on the theoretical side, I present sufficient and necessary identifiability conditions for structured and hierarchical latent attribute models. Under the attribute hierarchy, the identifiability results sharply characterize the different impacts on identifiability cast by different attributes in the graph. The developed identifiability conditions advance the theoretical knowledge and provide insights into real designs of diagnostic tests. Methodologically, I propose a statistically consistent method to select significant latent patterns and estimate the attribute hierarchy graph in high dimensions. An application of the method to data from an international educational assessment reveals meaningful knowledge structures of the student population. This is joint work with Gongjun Xu.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"><strong>Tuesday, August 25</strong></span><span style="font-family: Lato;"><strong>th, 10pm in UTC and Wednesday, August 26th, 1pm in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_68" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_71" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; padding-left: 0; text-indent: 0;">Didong Li (Duke): <span style="font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;">Learning & Exploiting Low-Dimensional Structure in High-Dimensional Data</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_73" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2F4ssfyqsqxj0pq1m%2FBernoulli2020_DidongLi.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw05V0gmD8pnLQxtrUWeXXJf" target="_blank">Slides can be found here</a></span>, <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://youtu.be/8q0utOo9zKs" target="_blank">video here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;">Abstract: <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Data lying in a high-dimensional ambient space are commonly thought to have a much lower intrinsic dimension. In particular, the data may be concentrated near a lower dimensional subspace or manifold. There is an immense literature focused on approximating the unknown subspace and the unknown density, and exploiting such approximations in clustering, data compression, and building of predictive models. Most of the literature relies on approximating subspaces and densities using a locally linear, and potentially multi-scale, dictionary with Gaussian kernels. We propose a simple and general alternative, which instead uses pieces of spheres, or spherelets, to locally approximate the unknown subspace. I will also introduce a curved kernel called the the Fisher–Gaussian (FG) kernel which outperforms multivariate Gaussians in many cases. Theory is developed showing that spherelets can approximate the unknown manifold with smaller covering numbers and the posterior consistency of the Dirichlet process mixture of FG kernels. Results relative to state-of-the-art competitors show gains in ability to accurately approximate the subspace and the density with fewer components and parameters. Time permitting, I will also present some applications of spherelets, including classification, geodesic distance estimation and clustering. </span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; padding-left: 0; text-indent: 0;"><span style="font-family: Lato;"><strong>Tuesday, August 25th, 9pm in UTC and Wednesday, August 26th, 12pm in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_80" class="yaqOZd lQAHbd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_83" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-indent: 0;">Ashwin Pananjady (Berkeley): <span style="font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;">Flexible models for learning from people: Statistics meets computation </span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_85" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://youtu.be/WyphZ3OB3i0" target="_blank">Video is available here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;">Abstract: <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">A plethora of latent variable models are used to learn from data generated by people. Specific examples include the Bradley--Terry--Luce and multinomial logit models for comparison and choice data, the Dawid--Skene model for crowdsourced question answering, and the Rasch model for categorical data that arises in psychometric analysis. In this talk, I will present a class of "permutation-based" models that borrows from the literature on sociology and economics and significantly generalizes classical approaches in these contexts, thereby improving their robustness to mis-specification. The talk will focus on the mathematical statistics of fitting these models, and describe a methodological toolbox that is inspired by considerations of adaptation as well as computation. These considerations highlight connections between the theory of adaptation in nonparametric statistics and conjectures in average-case computational complexity.</span> <span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">This talk will present vignettes from two papers, one jointly with Cheng Mao and Martin Wainwright, and another jointly with Richard Samworth.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-indent: 0;"><span style="font-family: Lato;"><strong>Monday, August 24th, 10pm in UTC and Tuesday, August 25th, 6am in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_36" class="yaqOZd qeLZfd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.76e1d8ac831fa0a1_39" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><div id="h.yictdvic7mtd" class="GV3q8e aP9Z7e"></div><h3 id="h.yictdvic7mtd_l" dir="ltr" class="CDt4Ke zfr3Q OmQG5e" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;" tabindex="-1"><div jscontroller="Ae65rd" jsaction="touchstart:UrsOsc; click:KjsqPd; focusout:QZoaZ; mouseover:y0pDld; mouseout:dq0hvd;fv1Rjc:jbFSOd;CrfLRd:SzACGe;" class="CjVfdc"><div class="PPhIP rviiZ" jsname="haAclf"><div role="presentation" class="U26fgb mUbCce fKz7Od LRAOtb Znu9nd M9Bg4d" jscontroller="mxS5xe" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-describedby="h.yictdvic7mtd_l" aria-label="Copy heading link" aria-disabled="false" data-tooltip="Copy heading link" aria-hidden="true" data-tooltip-position="top" data-tooltip-vertical-offset="12" data-tooltip-horizontal-offset="0"><a class="FKF6mc TpQm9d" href="#h.yictdvic7mtd" aria-label="Copy heading link" jsname="hiK3ld" role="button" aria-describedby="h.yictdvic7mtd_l"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -11px"><svg class="OUGEr QdAdhf" width="22px" height="22px" viewBox="0 0 24 24" fill="currentColor" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"/></svg></span></span></a></div></div><span class=" OGiC0d" style="font-style: normal; text-decoration: normal; vertical-align: baseline;">Tweedie New Researcher Award</span></div></h3></div></div></div></div></div></div></div></div></div></section><section id="h.76e1d8ac831fa0a1_74" class="yaqOZd qeLZfd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc yYI8W HQwdzb"><div class="JNdkSc-SmKAyb LkDMRd"><div class="vhaaFf qUO6Ue" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me" jsaction="click:uYnbT;JIbuQc:uYnbT;"><div id="h.76e1d8ac831fa0a1_77" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; font-weight: normal; text-decoration: normal; vertical-align: baseline;">Adel Javanmard (Los Angeles): Reliable Statistical Inference for High-Dimensional Models</span></p></div></div><div role="button" class="uArJ5e Y5FYJe cjq2Db zGbri" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Expand" tabindex="0" data-tooltip="Expand" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M5.41 7.59L4 9l8 8 8-8-1.41-1.41L12 14.17"/></svg></span></span></span></div><div role="button" class="uArJ5e Y5FYJe cjq2Db amZmwc" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-label="Collapse" tabindex="0" data-tooltip="Collapse" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="PDXc1b MbhUzd" jsname="ksKsZd"></div><span jsslot class="XuQwKc"><span class="GmuOkf"><span class="DPvwYc Vtm4Z" aria-hidden="true"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M18.59 16.41L20 15l-8-8-8 8 1.41 1.41L12 9.83"/></svg></span></span></span></div></div></div><div class="oKdM2c ZZyype"><div id="h.76e1d8ac831fa0a1_79" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2Fxx6h3j3c8ekcs97%2FIMS_Javanmard.pdf%3Fdl%3D0&sa=D&sntz=1&usg=AOvVaw3um0-c6TKQu1gkdUBOEvk0" target="_blank">Slides are available here</a></span>, <span class=" aw5Odc" style="text-decoration: underline;"><a class="XqQF9c" href="https://www.youtube.com/watch?v=rQ0mMxtwJl4&list=PLidqLPRgLpiMZBmdgCfa3L4MeQoOnPjFf&index=10&t=0s" target="_blank">video here</a></span>.</p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 0; padding-left: 0; text-align: left; text-indent: 0;"><span style="font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;">Abstract: We are living an era of data deluge where the ever-increasing complexity of datasets and algorithms has made machine learning systems less interpretable, turning them into ‘blackbox’ algorithms. As such there is legitimate concern about the reliability of algorithms and the reproducibility of findings which inform important decisions impacting people’s lives. An important step towards reproducibility is proper assessment of the uncertainty associated with estimations and predictions made by statistical algorithms. A popular approach to tackle this problem in a high-dimensional setting is via a novel method called 'debaising'. After reviewing the basic ideas underlying this approach, we discuss some of the major extensions and methodological developments that rely on the debiasing approach. In particular, we consider a setting of adaptive data collection which induces correlation in samples and bias in the estimates, posing additional obstacles to statistical inference. We introduce 'online debiasing' as an approach to overcome these problems and discuss its applications in time series analysis.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="margin-left: 0; margin-right: 17pt; padding-left: 0; text-indent: 0;"><span style="font-family: Lato; font-size: 11pt; font-style: normal; text-decoration: normal; vertical-align: baseline;"><strong>Friday, Au</strong></span><span style="font-family: Lato;"><strong>gust 28th, 7am in UTC and 2pm in UTC in the "</strong></span><span class=" aw5Odc" style="font-family: Lato; text-decoration: underline;"><a class="XqQF9c" href="/program/zoom-rooms"><strong>Conference hall</strong></a></span><span style="font-family: Lato;"><strong>"</strong></span></p></div></div></div></div></div></div></div></div></div></section></div><div class="Xpil1b xgQ6eb"></div><div jscontroller="j1RDQb" jsaction="rcuQ6b:rcuQ6b;MxH79b:JdcaS;FaOgy:XuHpsb;" class="dZA9kd ynRLnc" data-last-updated-at-time="1598942765971" data-is-preview="false"><div role="button" class="U26fgb JRtysb WzwrXb I12f0b K2mXPb zXBiaf ynRLnc" jscontroller="iSvg6e" jsaction="click:cOuCgd; 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