<div dir="ltr"><div dir="ltr"><div class="gmail_default" style="font-size:small"><p style="color:rgb(80,0,80);font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b>    </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit">  Wednesday, March 10th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="color:rgb(0,0,0);vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b>     </font></font><font color="#000000">Zoom Virtual Talk (</font><font color="#0000ff"><b><a href="https://uchicagogroup.zoom.us/webinar/register/WN_sQlwfNDJRB2lp8s1ARxV9w" target="_blank">register in advance here</a></b></font><font color="#000000">)</font></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>       </font></font></font>Aditi Raghunathan, Stanford University</p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Title:</b>        Rethinking the Role of Data in Robust Machine Learning</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"> </span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Abstract:</b> Despite notable successes on several carefully controlled benchmarks, current machine learning (ML) systems are remarkably brittle, raising serious concerns about their deployment in safety-critical applications like self-driving cars and predictive healthcare. In this talk, I discuss fundamental obstacles to building robust ML systems and develop principled approaches that form the foundations of robust ML. In particular, I will focus on the role of data and demonstrate the need to question common assumptions when improving robustness to (i) adversarial examples and (ii) spurious correlations. On the one hand, I will describe how and why naively using more data can surprisingly hurt performance in these settings. On the other hand, I will show that unlabeled data, when harnessed in the right fashion, is extremely beneficial and achieves state-of-the-art robustness. In closing, I will discuss how to build on the foundations of robust ML and achieve wide-ranging robustness in various domains including natural language processing and vision.</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Bio:</b> Aditi Raghunathan is a fifth year PhD student at Stanford University advised by Percy Liang. She is interested in building robust machine learning systems with guarantees for trustworthy real-world deployment. Her research in robustness has been recognized by a Google PhD Fellowship in Machine Learning and the Open Philanthropy AI Fellowship. Among other honors, she is also the recipient of the Anita Borg Memorial Scholarship and the Stanford School of Engineering Fellowship.</span><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;color:rgb(80,0,80);line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><b>Host:</b> <a href="mailto:mcallester@ttic.edu" target="_blank"><b>David McAllester</b></a></font></span></p><br class="gmail-Apple-interchange-newline"></div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small"><br></div><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL  60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Mar 10, 2021 at 10:10 AM Mary Marre <<a href="mailto:mmarre@ttic.edu">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b>    </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit">  Wednesday, March 10th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="color:rgb(0,0,0);vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b>     </font></font><font color="#000000">Zoom Virtual Talk (</font><font color="#0000ff"><b><a href="https://uchicagogroup.zoom.us/webinar/register/WN_sQlwfNDJRB2lp8s1ARxV9w" target="_blank">register in advance here</a></b></font><font color="#000000">)</font></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>       </font></font></font>Aditi Raghunathan, Stanford University</p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Title:</b>        Rethinking the Role of Data in Robust Machine Learning</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"> </span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Abstract:</b> Despite notable successes on several carefully controlled benchmarks, current machine learning (ML) systems are remarkably brittle, raising serious concerns about their deployment in safety-critical applications like self-driving cars and predictive healthcare. In this talk, I discuss fundamental obstacles to building robust ML systems and develop principled approaches that form the foundations of robust ML. In particular, I will focus on the role of data and demonstrate the need to question common assumptions when improving robustness to (i) adversarial examples and (ii) spurious correlations. On the one hand, I will describe how and why naively using more data can surprisingly hurt performance in these settings. On the other hand, I will show that unlabeled data, when harnessed in the right fashion, is extremely beneficial and achieves state-of-the-art robustness. In closing, I will discuss how to build on the foundations of robust ML and achieve wide-ranging robustness in various domains including natural language processing and vision.</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Bio:</b> Aditi Raghunathan is a fifth year PhD student at Stanford University advised by Percy Liang. She is interested in building robust machine learning systems with guarantees for trustworthy real-world deployment. Her research in robustness has been recognized by a Google PhD Fellowship in Machine Learning and the Open Philanthropy AI Fellowship. Among other honors, she is also the recipient of the Anita Borg Memorial Scholarship and the Stanford School of Engineering Fellowship.</span><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><b>Host:</b> <a href="mailto:mcallester@ttic.edu" target="_blank"><b>David McAllester</b></a></font></span></p><br></div><div style="font-size:small"><br></div><div style="font-size:small"><br></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL  60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Tue, Mar 9, 2021 at 3:48 PM Mary Marre <<a href="mailto:mmarre@ttic.edu" target="_blank">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b>    </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit">  Wednesday, March 10th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="color:rgb(0,0,0);vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b>     </font></font><font color="#000000">Zoom Virtual Talk (</font><font color="#0000ff"><b><a href="https://uchicagogroup.zoom.us/webinar/register/WN_sQlwfNDJRB2lp8s1ARxV9w" target="_blank">register in advance here</a></b></font><font color="#000000">)</font></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>       </font></font></font>Aditi Raghunathan, Stanford University</p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Title:</b>        Rethinking the Role of Data in Robust Machine Learning</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"> </span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Abstract:</b> Despite notable successes on several carefully controlled benchmarks, current machine learning (ML) systems are remarkably brittle, raising serious concerns about their deployment in safety-critical applications like self-driving cars and predictive healthcare. In this talk, I discuss fundamental obstacles to building robust ML systems and develop principled approaches that form the foundations of robust ML. In particular, I will focus on the role of data and demonstrate the need to question common assumptions when improving robustness to (i) adversarial examples and (ii) spurious correlations. On the one hand, I will describe how and why naively using more data can surprisingly hurt performance in these settings. On the other hand, I will show that unlabeled data, when harnessed in the right fashion, is extremely beneficial and achieves state-of-the-art robustness. In closing, I will discuss how to build on the foundations of robust ML and achieve wide-ranging robustness in various domains including natural language processing and vision.</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Bio:</b> Aditi Raghunathan is a fifth year PhD student at Stanford University advised by Percy Liang. She is interested in building robust machine learning systems with guarantees for trustworthy real-world deployment. Her research in robustness has been recognized by a Google PhD Fellowship in Machine Learning and the Open Philanthropy AI Fellowship. Among other honors, she is also the recipient of the Anita Borg Memorial Scholarship and the Stanford School of Engineering Fellowship.</span><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><b>Host:</b> <a href="mailto:mcallester@ttic.edu" target="_blank"><b>David McAllester</b></a></font></span></p><br></div><div style="font-size:small"><br></div><div style="font-size:small"><br></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL  60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Thu, Mar 4, 2021 at 1:40 PM Mary Marre <<a href="mailto:mmarre@ttic.edu" target="_blank">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div><p style="font-size:small;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b>    </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit">  Wednesday, March 10th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="font-size:small;margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="font-size:small;margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="color:rgb(0,0,0);vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b>     </font></font><font color="#000000">Zoom Virtual Talk (</font><font color="#0000ff"><b><a href="https://uchicagogroup.zoom.us/webinar/register/WN_sQlwfNDJRB2lp8s1ARxV9w" target="_blank">register in advance here</a></b></font><font color="#000000">)</font></font></p><p class="MsoNormal" style="font-size:small;margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"> </font></p><p class="MsoNormal" style="font-size:small;margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif" color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>       </font></font></font>Aditi Raghunathan, Stanford University</p><p class="MsoNormal" style="font-size:small;margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="font-size:small;margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Title:</b>        Rethinking the Role of Data in Robust Machine Learning</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"> </span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Abstract:</b> Despite notable successes on several carefully controlled benchmarks, current machine learning (ML) systems are remarkably brittle, raising serious concerns about their deployment in safety-critical applications like self-driving cars and predictive healthcare. In this talk, I discuss fundamental obstacles to building robust ML systems and develop principled approaches that form the foundations of robust ML. In particular, I will focus on the role of data and demonstrate the need to question common assumptions when improving robustness to (i) adversarial examples and (ii) spurious correlations. On the one hand, I will describe how and why naively using more data can surprisingly hurt performance in these settings. On the other hand, I will show that unlabeled data, when harnessed in the right fashion, is extremely beneficial and achieves state-of-the-art robustness. In closing, I will discuss how to build on the foundations of robust ML and achieve wide-ranging robustness in various domains including natural language processing and vision.</span><span style="letter-spacing:0.2px"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><br style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"></span><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><b>Bio:</b> Aditi Raghunathan is a fifth year PhD student at Stanford University advised by Percy Liang. She is interested in building robust machine learning systems with guarantees for trustworthy real-world deployment. Her research in robustness has been recognized by a Google PhD Fellowship in Machine Learning and the Open Philanthropy AI Fellowship. Among other honors, she is also the recipient of the Anita Borg Memorial Scholarship and the Stanford School of Engineering Fellowship.</span><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><br></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif"><b>Host:</b> <a href="mailto:mcallester@ttic.edu" target="_blank"><b>David McAllester</b></a></font></span></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span style="color:rgb(32,33,36);font-variant-ligatures:no-contextual"><font face="arial, sans-serif"><br></font></span></p></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif"><br></font></div><div dir="ltr"><font face="arial, helvetica, sans-serif"><br></font></div><div dir="ltr"><font face="arial, helvetica, sans-serif"><br></font></div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL  60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
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