<!DOCTYPE html>
<html>
<head>
<meta http-equiv="content-type" content="text/html; charset=UTF-8">
</head>
<body>
<p>Reminder for the DS seminar tomorrow Friday at noon in the MRB
seminar room; please use the link below to register if you plan to
attend.</p>
<p>Best,</p>
<p>V. Tsotras<br>
</p>
<div class="moz-forward-container"><br>
<br>
-------- Forwarded Message --------
<table class="moz-email-headers-table" cellspacing="0"
cellpadding="0" border="0">
<tbody>
<tr>
<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Subject:
</th>
<td>[UCR_DataScience] Data Science talk by Prof. Alfonso
Landeros, Friday May 24h, 12-1pm, MRB Seminar Room</td>
</tr>
<tr>
<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Date: </th>
<td>Mon, 20 May 2024 16:23:23 -0700</td>
</tr>
<tr>
<th valign="BASELINE" nowrap="nowrap" align="RIGHT">From: </th>
<td>tsotras--- via DataScience
<a class="moz-txt-link-rfc2396E" href="mailto:datascience@lists.ucr.edu"><datascience@lists.ucr.edu></a></td>
</tr>
<tr>
<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Reply-To:
</th>
<td><a class="moz-txt-link-abbreviated" href="mailto:tsotras@cs.ucr.edu">tsotras@cs.ucr.edu</a></td>
</tr>
<tr>
<th valign="BASELINE" nowrap="nowrap" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:datascience@lists.ucr.edu">datascience@lists.ucr.edu</a></td>
</tr>
</tbody>
</table>
<br>
<br>
We will have a Data Science seminar this Friday, May 24th,
12:00-1:00pm at<br>
the MRB Seminar Room (1st floor).<br>
<br>
**** Pizza and refreshments will be provided ****<br>
<br>
To keep track of the number of attendees, please *register* at:<br>
<a class="moz-txt-link-freetext" href="https://www.eventbrite.com/e/data-science-talk-tickets-910003584217">https://www.eventbrite.com/e/data-science-talk-tickets-910003584217</a><br>
<br>
The talk will be given by Prof. Alfonso Landeros, Statistics
Department, UCR<br>
<br>
TITLE:<br>
"The Proximal Distance Principle for Constrained Estimation"<br>
<br>
<br>
ABSTRACT:<br>
Statistical methods often involve solving an optimization problem,
such as<br>
in maximum likelihood estimation and regression. The addition of<br>
constraints, either to enforce a hard requirement in estimation or
to<br>
regularize solutions, complicates matters. Fortunately, the rich
theory of<br>
convex optimization provides ample tools for devising novel
methods. In<br>
this talk, I present applications of distance-to-set penalties to<br>
statistical learning problems. Specifically, I will focus on
proximal<br>
distance algorithms, based on the MM principle, tailored to
various<br>
applications such as regression and discriminant analysis. Special<br>
emphasis is given to sparsity set constraints as a compromise
between<br>
exhaustive combinatorial searches and lasso penalization methods
that<br>
induce shrinkage.<br>
<br>
<br>
------------------------------------<br>
Sponsored by the UCR Data Science Center, the purpose of the Data
Science<br>
Seminars is to foster collaborations between "core" Data Science
faculty<br>
(from CSE/ECE/Stat Departments) and faculty/visitors from other
sciences<br>
that face Data Science problems in their research. These informal<br>
gatherings are open to interested faculty and graduate students.
Each<br>
meeting will start with a talk describing research problems and
then a<br>
discussion will follow for questions, open problems, ideas for
possible<br>
collaborations etc.<br>
<br>
A full list of previous seminars appears at:<br>
<a class="moz-txt-link-freetext" href="http://datascience.ucr.edu/seminars">http://datascience.ucr.edu/seminars</a><br>
<br>
Forward this email to other colleagues or graduate students in
your lab<br>
that may be interested. Moreover, if you are interested in giving
a Data<br>
Science related talk, please contact me (<a class="moz-txt-link-abbreviated" href="mailto:tsotras@cs.ucr.edu">tsotras@cs.ucr.edu</a>).<br>
<br>
Sincerely,<br>
Vassilis Tsotras<br>
Professor, CSE Department<br>
co-Director, Data Science Major<br>
Director, MS in Computational Data Science<br>
<br>
<br>
</div>
</body>
</html>