<div dir="ltr"><div dir="ltr"><div class="gmail_default" style="font-size:small"><div class="gmail_default"><div class="gmail_default"><div class="gmail_default"><div class="gmail_default"><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-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"> Friday, February 7th at 10:30am</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"> </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="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b>    </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit">TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526</font></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"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>      </font></font>Yixin Wang, Columbia University</font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><b>Title:</b>       </font><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif">The Blessings of Multiple Causes</font></span><br></p></div></div><font face="arial, sans-serif"><br><b>Abstract: </b>Causal inference from observational data is a vital problem, but it comes with strong assumptions. Most methods assume that we observe all confounders, variables that affect both the causal variables and the outcome variables. But whether we have observed all confounders is a famously untestable assumption. We describe the deconfounder, a way to do causal inference from observational data allowing for unobserved confounding. How does the deconfounder work? The deconfounder is designed for problems of multiple causal inferences: scientific studies that involve many causes whose effects are simultaneously of interest. The deconfounder uses the correlation among causes as evidence for unobserved confounders, combining unsupervised machine learning and predictive model checking to perform causal inference. We study the theoretical requirements for the deconfounder to provide unbiased causal estimates, along with its limitations and tradeoffs. We demonstrate the deconfounder on real-world data and simulation studies.  </font></div><div class="gmail_default"><font face="arial, sans-serif"><br></font></div><div class="gmail_default"><font face="arial, sans-serif"><b>Bio:</b> </font>Yixin Wang is a PhD student in the Statistics Department of Columbia University, advised by Professor David Blei. Her research interests lie in Bayesian statistics, machine learning, and causal inference. Prior to Columbia, she completed undergraduate studies in</div>mathematics and computer science at the Hong Kong University of Science and Technology. Her research has received several awards, including the INFORMS data mining best paper award, student paper awards from American Statistical Association Biometrics Section and Bayesian Statistics Section, and the ICSA conference young researcher award.</div><div class="gmail_default"><br></div><div class="gmail_default"><br><div class="gmail_default"><span style="font-family:arial,sans-serif"><b>Host:</b> </span><a href="mailto:klivescu@ttic.edu" target="_blank" style="font-family:arial,sans-serif">Karen Livescu</a><br></div><div class="gmail_default"><br></div><div class="gmail_default"><br></div><div class="gmail_default"><i style="font-family:arial,sans-serif;font-size:large;color:rgb(11,83,148)"><a href="https://www.uchicago.edu/" target="_blank" style="box-sizing:border-box;margin:0px;padding:0px;border:0px;outline:0px;background:transparent;vertical-align:baseline;text-decoration-line:none">University of Chicago </a>and</i><i style="font-family:arial,sans-serif;font-size:large;color:rgb(11,83,148)"> <a href="http://www.ttic.edu/" target="_blank" style="box-sizing:border-box;margin:0px;padding:0px;border:0px;outline:0px;background:transparent;vertical-align:baseline;text-decoration-line:none">Toyota Technological Institute at Chicago</a></i><br></div><div class="gmail_default"><h2 style="box-sizing:border-box;margin:0px;padding:0px 0px 10px;border:0px;outline:0px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;color:rgb(51,51,51);line-height:1em"><font size="2" face="verdana, sans-serif"><a href="https://voices.uchicago.edu/machinelearning/events/" target="_blank">Machine Learning Seminar Series</a></font></h2><h6 style="font-size:14px;box-sizing:border-box;margin:0px;padding:0px 0px 10px;border:0px;outline:0px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-weight:500;line-height:1em;font-family:Montserrat,Helvetica,Arial,Lucida,sans-serif"><br></h6></div></div></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 Thu, Feb 6, 2020 at 2:41 PM 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><div style="font-size:small"><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-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"> Friday, February 7th at 10:30am</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"> </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="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b>    </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit">TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526</font></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"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>      </font></font>Yixin Wang, Columbia University</font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><b>Title:</b>       </font><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif">The Blessings of Multiple Causes</font></span><br></p></div></div><font face="arial, sans-serif"><br><b>Abstract: </b>Causal inference from observational data is a vital problem, but it comes with strong assumptions. Most methods assume that we observe all confounders, variables that affect both the causal variables and the outcome variables. But whether we have observed all confounders is a famously untestable assumption. We describe the deconfounder, a way to do causal inference from observational data allowing for unobserved confounding. How does the deconfounder work? The deconfounder is designed for problems of multiple causal inferences: scientific studies that involve many causes whose effects are simultaneously of interest. The deconfounder uses the correlation among causes as evidence for unobserved confounders, combining unsupervised machine learning and predictive model checking to perform causal inference. We study the theoretical requirements for the deconfounder to provide unbiased causal estimates, along with its limitations and tradeoffs. We demonstrate the deconfounder on real-world data and simulation studies.  </font></div><div style="font-size:small"><font face="arial, sans-serif"><br></font></div><div style="font-size:small"><font face="arial, sans-serif"><b>Bio:</b> </font>Yixin Wang is a PhD student in the Statistics Department of Columbia University, advised by Professor David Blei. Her research interests lie in Bayesian statistics, machine learning, and causal inference. Prior to Columbia, she completed undergraduate studies in</div>mathematics and computer science at the Hong Kong University of Science and Technology. Her research has received several awards, including the INFORMS data mining best paper award, student paper awards from American Statistical Association Biometrics Section and Bayesian Statistics Section, and the ICSA conference young researcher award.</div><div><br></div><div><br><div style="font-size:small"><span style="font-family:arial,sans-serif"><b>Host:</b> </span><a href="mailto:klivescu@ttic.edu" style="font-family:arial,sans-serif" target="_blank">Karen Livescu</a><br></div><div style="font-size:small"><br></div><div style="font-size:small"><br></div><div style="font-size:small"><i style="font-family:arial,sans-serif;font-size:large;color:rgb(11,83,148)"><a href="https://www.uchicago.edu/" style="box-sizing:border-box;margin:0px;padding:0px;border:0px;outline:0px;background:transparent;vertical-align:baseline;text-decoration-line:none" target="_blank">University of Chicago </a>and</i><i style="font-family:arial,sans-serif;font-size:large;color:rgb(11,83,148)"> <a href="http://www.ttic.edu/" style="box-sizing:border-box;margin:0px;padding:0px;border:0px;outline:0px;background:transparent;vertical-align:baseline;text-decoration-line:none" target="_blank">Toyota Technological Institute at Chicago</a></i><br></div><div style="font-size:small"><h2 style="box-sizing:border-box;margin:0px;padding:0px 0px 10px;border:0px;outline:0px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;color:rgb(51,51,51);line-height:1em"><font size="2" face="verdana, sans-serif"><a href="https://voices.uchicago.edu/machinelearning/events/" target="_blank">Machine Learning Seminar Series</a></font></h2><h6 style="font-size:14px;box-sizing:border-box;margin:0px;padding:0px 0px 10px;border:0px;outline:0px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-weight:500;line-height:1em;font-family:Montserrat,Helvetica,Arial,Lucida,sans-serif"><br></h6></div><div style="font-size:small"><br></div></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 Sat, Feb 1, 2020 at 2:55 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 style="font-size:small"><div><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-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"> Friday, February 7th at 10:30am</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"> </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="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b>    </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit">TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526</font></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"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b>      </font></font>Yixin Wang, Columbia University</font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;text-align:justify;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"><b>Title:</b>       </font><span style="color:rgb(60,64,67);letter-spacing:0.2px;white-space:pre-wrap"><font face="arial, sans-serif">The Blessings of Multiple Causes</font></span><br></p></div></div><font face="arial, sans-serif"><br><b>Abstract: </b>Causal inference from observational data is a vital problem, but it comes with strong assumptions. Most methods assume that we observe all confounders, variables that affect both the causal variables and the outcome variables. But whether we have observed all confounders is a famously untestable assumption. We describe the deconfounder, a way to do causal inference from observational data allowing for unobserved confounding. How does the deconfounder work? The deconfounder is designed for problems of multiple causal inferences: scientific studies that involve many causes whose effects are simultaneously of interest. The deconfounder uses the correlation among causes as evidence for unobserved confounders, combining unsupervised machine learning and predictive model checking to perform causal inference. We study the theoretical requirements for the deconfounder to provide unbiased causal estimates, along with its limitations and tradeoffs. We demonstrate the deconfounder on real-world data and simulation studies.  </font></div><div><font face="arial, sans-serif"><br></font></div><div><span style="font-family:arial,sans-serif"><b>Host:</b> </span><a href="mailto:klivescu@ttic.edu" style="font-family:arial,sans-serif" target="_blank">Karen Livescu</a><br></div><div><br></div><div><br></div><div><i style="font-family:arial,sans-serif;font-size:large;color:rgb(11,83,148)"><a href="https://www.uchicago.edu/" style="box-sizing:border-box;margin:0px;padding:0px;border:0px;outline:0px;background:transparent;vertical-align:baseline;text-decoration-line:none" target="_blank">University of Chicago </a>and</i><i style="font-family:arial,sans-serif;font-size:large;color:rgb(11,83,148)"> <a href="http://www.ttic.edu/" style="box-sizing:border-box;margin:0px;padding:0px;border:0px;outline:0px;background:transparent;vertical-align:baseline;text-decoration-line:none" target="_blank">Toyota Technological Institute at Chicago</a></i><br></div><div><h2 style="box-sizing:border-box;margin:0px;padding:0px 0px 10px;border:0px;outline:0px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;color:rgb(51,51,51);line-height:1em"><font size="2" face="verdana, sans-serif"><a href="https://voices.uchicago.edu/machinelearning/events/" target="_blank"><span>Machine</span> <span>Learning</span> Seminar <span>Series</span></a></font></h2><h6 style="font-size:14px;box-sizing:border-box;margin:0px;padding:0px 0px 10px;border:0px;outline:0px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-weight:500;line-height:1em;font-family:Montserrat,Helvetica,Arial,Lucida,sans-serif"><font color="#333333">Sign up for announcement email list at </font><a href="https://lists.uchicago.edu/web/subscribe/ml-announce." target="_blank"><font color="#0000ff"><span style="box-sizing:border-box;border-style:initial;border-color:initial;outline-color:initial;outline-style:initial;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">https://lists.uchicago.edu/web/subscribe/ml-announc</span></font></a></h6></div><div><br></div><div><br></div><div><span style="font-family:arial,helvetica,sans-serif">Mary C. Marre</span><br></div></div><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><font face="arial, helvetica, sans-serif">Administrative Assistant</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>
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