<div dir="ltr"><div dir="ltr"><div><div class="gmail_default" style="font-family:georgia,serif;font-size:small;color:rgb(0,0,0)"><div><div class="gmail_default"><font face="georgia, serif"><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">    Monday, March 31st at <b style="background-color:rgb(255,255,0)">11:30am CT</b><b> </b></font></font></font></div><div class="gmail_default"><font face="georgia, serif" color="#000000"></font></div><div class="gmail_default"><font face="georgia, serif" color="#000000"><b>Where:       </b>Talk will be given <font style="font-weight:bold"><u>live, in-person</u></font><font style="font-weight:bold"> </font>at</font></div><p class="MsoNormal" style="margin:0in;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="georgia, serif" color="#000000">                       TTIC, 6045 S. Kenwood Avenue</font></p><p class="MsoNormal" style="margin:0in;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font color="#000000" face="georgia, serif">                       5th Floor, Room 530<b> </b></font></p><p class="MsoNormal" style="margin:0in;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><b><font face="georgia, serif" color="#000000"><br></font></b></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="georgia, serif" color="#000000"><b style="letter-spacing:0.2px">Virtually:</b><span style="letter-spacing:0.2px">  via Panopto </span>(<a href="https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=3436bdc7-3be8-40f9-a8a3-b248011f659c" target="_blank">livestream</a><span style="letter-spacing:0.2px">)</span><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="georgia, serif" color="#000000"><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="georgia, serif"><font color="#000000"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>         </font></font></font>Masashi Sugiyama<span class="gmail_default">, RIKEN/The University of Tokyo</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"></p><div><p style="letter-spacing:0.2px"><font face="georgia, serif"><font color="#000000"><span style="letter-spacing:normal"><b>Title:</b>          </span></font><span style="letter-spacing:normal">Machine Learning from Weak, Noisy, and Biased Supervision</span></font></p><div><font face="georgia, serif"><font color="#000000"><b>Abstract:  </b></font>In m<span class="gmail_default"></span>any machine learning applications, it is often challenging to collect a large amount of high-quality labeled data. However, learning from unlabeled data is not necessarily reliable. To overcome this problem, the use of imperfect data is promising. In this talk, I will review our recent research on reliable machine learning from imperfect supervision, including weakly supervised learning, noisy label learning, and transfer learning. Finally, I will discuss how machine learning research should evolve in the era of large foundation models.</font></div><div><font face="georgia, serif" color="#000000"><br></font></div><div><font face="georgia, serif"><font color="#000000"><b>Short Bio</b>: </font>Masashi Sugiyama received his Ph.D. in Computer Science from Tokyo Institute of Technology, Japan, in 2001. After serving as an assistant and associate professor at the same institute, he became a professor at the University of Tokyo in 2014. Since 2016, he has also served as the director of the RIKEN Center for Advanced Intelligence Project. His research interests include theories and algorithms of machine learning. He was awarded the Japan Academy Medal in 2017 and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology of Japan in 2022.</font></div><div><font face="georgia, serif"><br></font></div><font face="georgia, serif"><a href="https://scholar.google.co.jp/citations?user=GkYIrlIAAAAJ" target="_blank">https://scholar.google.co.jp/citations?user=GkYIrlIAAAAJ</a></font></div><div><br><b>Host:<span class="gmail_default"> <a href="mailto:nati@ttic.edu" target="_blank">Nati Srebro</a></span></b></div></div><div><br></div><span class="gmail_signature_prefix">--</span><br><div dir="ltr" class="gmail_signature"><div dir="ltr"><b style="color:rgb(34,34,34);font-family:Arial,Helvetica,sans-serif"><font color="#3d85c6">Brandie Jones </font></b><div style="color:rgb(34,34,34);font-family:Arial,Helvetica,sans-serif"><div><div><font color="#3d85c6"><b><i>Executive </i></b></font><b style="color:rgb(61,133,198)"><i>Administrative Assistant</i></b></div></div><div><font color="#3d85c6">Toyota Technological Institute</font></div><div><font color="#3d85c6">6045 S. Kenwood Avenue</font></div><div><font color="#3d85c6">Chicago, IL  60637</font></div></div><div style="color:rgb(34,34,34);font-family:Arial,Helvetica,sans-serif"><font color="#3d85c6"><a href="http://www.ttic.edu/" target="_blank">www.ttic.edu</a> </font></div><br></div></div></div></div></div>
</div>