<div dir="ltr"><div class="gmail_default" style="font-size:small">Hi All,</div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small">You are highly recommended to sign up for and attend this seminar.</div><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div style="margin:0px;padding:0px;border:0px;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:Calibri,Arial,Helvetica,sans-serif;vertical-align:baseline;color:black"><br></div><div style="margin:0px;padding:0px;border:0px;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:Calibri,Arial,Helvetica,sans-serif;vertical-align:baseline;color:black"></div></div></div></div><br><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">---------- Forwarded message ---------<br>From: <strong class="gmail_sendername" dir="auto">WNAR of IBS</strong> <span dir="auto"><<a href="mailto:wnar@wnar.org">wnar@wnar.org</a>></span><br>Date: Mon, Apr 24, 2023 at 4:13 PM<br>Subject: ANNOUNCEMENT: WNAR WEBINAR BY Cynthia Rudin, Duke University, 9:00am-10:am PDT, May 12, 2023<br>To: Wei Vivian Li <<a href="mailto:vivianlistat@gmail.com">vivianlistat@gmail.com</a>><br></div><br><br><div class="msg-8961025778011170709"><img src="https://wnar.org/EmailTracker/EmailTracker.ashx?emailCode=RKSzI0HMr7yeT84R%2bq%2fdrdXLfG87mOxsCXxCJjXMhLYEZSLdYhIY7fAdyUQPvMiYHV6m3%2fB5m8B2Ps1vFuzR9hhQWaLJTbpZ%2fSpg74jYH8E%3d" style="width:1px;height:1px;border:none" alt="">  <u></u>                                                   <div>       <div>     <table background="https://wnar.orgnone" bgcolor="transparent" align="center" border="0" cellpadding="0" cellspacing="0" height="100%" width="100%" style="background-image:none;background-color:transparent;background-position:50% 0%;background-repeat:repeat">   <tbody>    <tr>    <td align="center" valign="top">             <div style="margin:0px auto;max-width:600px">     <table align="center" border="0" cellpadding="0" cellspacing="0" role="presentation" style="width:100%">   <tbody>    <tr>    <td style="direction:ltr;font-size:0px;padding:0px;text-align:center">          <div class="m_-8961025778011170709mj-column-px-600" style="font-size:0px;text-align:left;direction:ltr;display:inline-block;vertical-align:top;width:100%">    <table border="0" cellpadding="0" cellspacing="0" role="presentation" width="100%">   <tbody>   <tr>    <td style="background-color:transparent;vertical-align:top;padding:0px">      <table border="0" cellpadding="0" cellspacing="0" role="presentation" width="100%">      <tbody><tr>    <td align="left" style="font-size:0px;padding:0px;word-break:break-word">      <div style="font-family:Arial,Helvetica Neue,Helvetica,sans-serif;font-size:14px;line-height:1;text-align:left;color:#000000"><p style="font-family:Arial,'Helvetica Neue',Helvetica,sans-serif;font-size:14px;margin-top:0;margin-bottom:14px;padding:0"><img src="http://www.wnar.org/resources/Pictures/logo.png" alt="" title="" border="0" style="height:auto;line-height:100%;outline:none;max-width:100%;text-decoration:none;width:auto" width="332"><br></p></div>     </td>    </tr>     </tbody></table>     </td>   </tr>   </tbody>  </table>   </div>        </td>    </tr>   </tbody>   </table>    </div>          <div style="margin:0px auto;max-width:600px">     <table align="center" border="0" cellpadding="0" cellspacing="0" role="presentation" style="width:100%">   <tbody>    <tr>    <td style="direction:ltr;font-size:0px;padding:0px;text-align:center">          <div class="m_-8961025778011170709mj-column-px-600" style="font-size:0px;text-align:left;direction:ltr;display:inline-block;vertical-align:top;width:100%">    <table border="0" cellpadding="0" cellspacing="0" role="presentation" width="100%">   <tbody>   <tr>    <td style="background-color:transparent;vertical-align:top;padding:0px">      <table border="0" cellpadding="0" cellspacing="0" role="presentation" width="100%">      <tbody><tr>    <td align="left" style="font-size:0px;padding:0px;word-break:break-word">      <div style="font-family:Arial,Helvetica Neue,Helvetica,sans-serif;font-size:14px;line-height:1;text-align:left;color:#000000"><p style="font-family:Arial,'Helvetica Neue',Helvetica,sans-serif;font-size:14px;margin-top:0;margin-bottom:14px;padding:0"><span style="background-color:white"><font face="Cambria, serif"><br></font></span></p>  <p align="center"><strong><font style="font-size:19px" color="#000000" face="Arial, sans-serif"></font></strong></p><p align="center"><strong><font style="font-size:13px" color="#000000" face="Arial, sans-serif">WNAR Webinar by Dr. Cynthia Rudin</font></strong></p> <p align="center"><font style="font-size:13px" face="Arial, sans-serif"><strong>Understanding How Dimension Reduction Tools Work</strong></font></p>  <p><span style="background-color:white"><font style="font-size:13px" color="#222222" face="Arial, sans-serif">It is a great pleasure to announce the upcoming WNAR Webinar by our distinguished colleague Dr. Cynthia Rudin from Duke University.</font></span> </p>  <p><strong><span style="background-color:white"><font style="font-size:13px" color="#222222" face="Arial, sans-serif">Time: 9:00am - 10:00am PDT (12:00 PM - 1:00 PM EDT), Friday May 12, 2023</font></span></strong> </p>  <p><strong><font style="font-size:13px" color="#222222" face="Arial, sans-serif">This is a free event and pre-</font></strong><strong><font style="font-size:13px" face="Arial, sans-serif">registration <span style="background-color:white"><font color="#222222">is required</font></span><font color="#222222"> at: </font></font></strong></p> <p><strong><span style="background-color:white"><font style="font-size:13px" color="#222222" face="Arial, sans-serif"><a href="https://wnar.org/EmailTracker/LinkTracker.ashx?linkAndRecipientCode=YyvlCDMuvWACMh0sZJTMVpHkIC1lQnTPwsT5vXCANNIdCkUgfR4r0P5D1LbEeMg0rqKBdPB93xx2TQ8Hjh28fOY%2bZ2ocCQ87D7Fw7JuvYlU%3d" target="_blank">https://www.eventbrite.com/e/623976609837</a></font></span></strong></p>  <p><strong><font style="font-size:13px" color="#222222" face="Arial, sans-serif">Zoom Dial-in information and webinar link will be sent 24 hours before the event.</font></strong> </p> <p><font style="font-size:13px" face="Arial, sans-serif">(<span style="background-color:white"><font color="#1155CC">C</font></span><span style="background-color:white"><font color="#1155CC">heck out <a href="https://wnar.org/EmailTracker/LinkTracker.ashx?linkAndRecipientCode=UpTOeRRjjjdyPI%2fEbxfOPRcL3DzAVBSMCmCnVNh7fni%2b9XnDZjaTNxsE2YHjwPBXlTVOm59O%2btPmUVo0dSQmLTFd4z2kU2oOlYp%2f15UieMM%3d" target="_blank">WNAR YouTube channel</a> for webinar recordings</font></span>)</font></p> <p><font style="font-size:13px" face="Arial, sans-serif">  </font></p> <p><strong><span style="background-color:white"><font style="font-size:13px" color="#222222" face="Arial, sans-serif">Abstract:</font></span></strong> </p> <p><font style="font-size:13px" face="Arial, sans-serif">Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMap have demonstrated impressive visualization performance on many real-world datasets. They are useful for understanding data and trustworthy decision-making, particularly for biological data. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: past methods can either handle one or the other, but not both. In this work, our main goal is to understand what aspects of DR methods are important for preserving both local and global structure: it is difficult to design a better method without a true understanding of the choices we make in our algorithms and their empirical impact on the lower-dimensional embeddings they produce. Towards the goal of local structure preservation, we provide several useful design principles for DR loss functions based on our new understanding of the mechanisms behind successful DR methods. Towards the goal of global structure preservation, our analysis illuminates that the choice of which components to preserve is important. We leverage these insights to design a new algorithm for DR, called Pairwise Controlled Manifold Approximation Projection (PaCMAP), which preserves both local and global structure. Our work provides several unexpected insights into what design choices both to make and avoid when constructing DR algorithms.</font></p>  <p><font style="font-size:13px" face="Arial, sans-serif">I will be discussing work from the following papers:</font></p>  <p><font style="font-size:13px" face="Arial, sans-serif">Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik</font></p> <p><font style="font-size:13px" face="Arial, sans-serif">Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization</font></p> <p><font style="font-size:13px" face="Arial, sans-serif">Journal of Machine Learning Research (JMLR), 2021</font></p> <p><font style="font-size:13px" face="Arial, sans-serif"><a href="https://wnar.org/EmailTracker/LinkTracker.ashx?linkAndRecipientCode=%2fSaqgXGt0%2fqawSDDT18H17MwJasHB3IT%2bLM21xSD7QqVvTf7ugLbFMfigFoZHV34Ozcy2x8Aw9NSbcC2%2bsJdknoQ6yhwhMpqyy41gb7gOqY%3d" target="_blank">https://jmlr.org/papers/v22/20-1061.html</a> </font></p>  <p><font style="font-size:13px" face="Arial, sans-serif">Haiyang Huang, Yingfan Wang, Cynthia Rudin, and Edward P. Browne</font></p> <p><font style="font-size:13px" face="Arial, sans-serif">Towards a Comprehensive Evaluation of Dimension Reduction Methods for Transcriptomic Data Visualization</font></p> <p><font style="font-size:13px" face="Arial, sans-serif">Communications Biology (Nature), 2022.</font></p> <p><font style="font-size:13px" face="Arial, sans-serif"><a href="https://wnar.org/EmailTracker/LinkTracker.ashx?linkAndRecipientCode=CukSJknLCs8I3717z%2bXKXLPWfQ3U1GAD2BsWYXX4YUNHRTNkc4Qh9joAIlijHlBNoYgtJOJDgiE4kf5rxagU8q0VT2JOnjMikY%2boquXQH20%3d" target="_blank">https://www.nature.com/articles/s42003-022-03628-x</a></font></p>  <p><strong><span style="background-color:white"><font style="font-size:13px" color="#222222" face="Arial, sans-serif">Speaker Bio:</font></span></strong></p> <p><font style="font-size:13px" face="Arial, sans-serif">Cynthia Rudin is a professor of computer science, electrical and computer engineering, statistical science, mathematics, and biostatistics & bioinformatics at Duke University, and directs the Interpretable Machine Learning Lab. Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She holds an undergraduate degree from the University at Buffalo, and a PhD from Princeton University. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI). This award is the most prestigious award in the field of artificial intelligence. Similar only to world-renowned recognitions, such as the Nobel Prize and the Turing Award, it carries a monetary reward at the million-dollar level. Prof. Rudin is also a three-time winner of the INFORMS Innovative Applications in Analytics Award, was named as one of the "Top 40 Under 40" by Poets and Quants in 2015, and was named by Businessinsider.com as one of the 12 most impressive professors at MIT in 2015, and is a 2022 Guggenheim Fellow. She is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and AAAI.</font></p>  <p><font style="font-size:13px" face="Arial, sans-serif">Prof. Rudin is the past chair of both the INFORMS Data Mining Section and the Statistical Learning and Data Science Section of the American Statistical Association. She has also served on committees for DARPA, the National Institute of Justice, AAAI, and ACM SIGKDD. She has served on several committees for the National Academies of Sciences, Engineering and Medicine, including the Committee on Applied and Theoretical Statistics, the Committee on Law and Justice, the Committee on Analytic Research Foundations for the Next-Generation Electric Grid, and the Committee on Facial Recognition Technology.  She has given keynote/plenary talks at several conferences including INFORMS, KDD (twice), AISTATS, SDM, ICDM, Machine Learning in Healthcare (MLHC), Fairness, Accountability and Transparency in Machine Learning (FAT-ML), ECML-PKDD, and the Nobel Conference. Her work has been featured in news outlets including the NY Times, Washington Post, Wall Street Journal, the Boston Globe, Businessweek, and NPR.</font></p>  <p><span style="background-color:white"><font style="font-size:13px" color="#969696" face="Arial, sans-serif">WNAR is the Western North American Region of </font></span><font style="font-size:13px" face="Arial, sans-serif"><a href="https://wnar.org/EmailTracker/LinkTracker.ashx?linkAndRecipientCode=dcqaZKIrgx143lJFcI4v8AhL6lm17pSwfB8u3oVhTOhWDuUSgDZt8YpaNMYSs3brGcoM%2fggDmu1W%2bTjQp24nOupuNBEHzKY2Xn28yZOUbuk%3d" target="_blank"><span style="background-color:white"><font color="#81B7FF">The International Biometric Society</font></span></a><span style="background-color:white"><font color="#969696">, an international professional and academic society promoting the development and application of statistical and mathematical theory and methods in the biosciences.  Visit </font></span><a href="https://wnar.org/EmailTracker/LinkTracker.ashx?linkAndRecipientCode=vKm1whwppWbqF%2f8ljuKxqMuVWJy87%2bFVAW8659x8okJQlftkdcjdAPyerHNxKuuSXEHzqbzta%2fdDjSdrHR4eGLosxj%2b8r5MJ5g3kpSprRLY%3d" target="_blank"><span style="background-color:white">www.wnar.org</span></a><span style="background-color:white"><font color="#969696"> for more details and events or follow us on </font></span><a href="https://wnar.org/EmailTracker/LinkTracker.ashx?linkAndRecipientCode=QZTP%2bXCQli5ARMRx3SddNLE6NOO6YzYRVrMR9wafkn4EI4S1Yc4jxAMcbi6rCVgA9nt8STy8mmm2%2bNdUOPhopAxp3d52feiNaHf8T%2fi%2b4Z8%3d" target="_blank"><span style="background-color:white"><font color="#1155CC">https://twitter.com/wnar_ibs</font></span></a><span style="background-color:white"><font color="#1155CC">. </font></span> </font></p><p style="font-family:Arial,'Helvetica Neue',Helvetica,sans-serif;font-size:14px;margin-top:0;margin-bottom:14px;padding:0"><br></p></div>     </td>    </tr>     </tbody></table>     </td>   </tr>   </tbody>  </table>   </div>        </td>    </tr>   </tbody>   </table>    </div>          <div style="margin:0px auto;max-width:600px">     <table align="center" border="0" cellpadding="0" cellspacing="0" role="presentation" style="width:100%">   <tbody>    <tr>    <td style="direction:ltr;font-size:0px;padding:0px;text-align:center">          <div class="m_-8961025778011170709mj-column-px-600" style="font-size:0px;text-align:left;direction:ltr;display:inline-block;vertical-align:top;width:100%">    <table border="0" cellpadding="0" cellspa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