<div dir="ltr">Hi all this is the pass code for the thesis proposal<br>629338<br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, Apr 18, 2022 at 10:21 AM Artur Dubrawski <<a href="mailto:awd@cs.cmu.edu">awd@cs.cmu.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">fun talk today!<br><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">---------- Forwarded message ---------<br>From: <strong class="gmail_sendername" dir="auto">Diane Stidle</strong> <span dir="auto"><<a href="mailto:stidle@andrew.cmu.edu" target="_blank">stidle@andrew.cmu.edu</a>></span><br>Date: Mon, Apr 18, 2022 at 9:58 AM<br>Subject: Reminder - Thesis Proposal - April 18, 2022 - Kin Gutierrez Olivares - Applied Mathematics of the Future or the Future of Forecast<br>To: <a href="mailto:ml-seminar@cs.cmu.edu" target="_blank">ml-seminar@cs.cmu.edu</a> <<a href="mailto:ML-SEMINAR@cs.cmu.edu" target="_blank">ML-SEMINAR@cs.cmu.edu</a>>,  <<a href="mailto:robstine@amazon.com" target="_blank">robstine@amazon.com</a>><br></div><br><br>
  
    
  
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    <p><i><b>Thesis Proposal</b></i></p>
    <p>Date: April 18, 2022<br>
      Time: 1:30pm (EDT) (Remote)<br>
      Speaker: Kin Gutierrez Olivares</p>
    <p><b>Title: Applied Mathematics of the Future or the Future of
        Forecast</b></p>
    <p>Abstract:<br>
      Novel learning algorithms have enhanced our ability to acquire
      knowledge solely from past observations of single events to learn
      from the observations of several related events. This ability to
      leverage shared useful information across time series is causing a
      paradigm shift in the time-series forecasting practice. <br>
      In this proposed thesis, we aim to advance time-series forecasting
      methods powered by machine learning and address some of the most
      pressing challenges that limit usability, usefulness, and
      attainable real-world impact of the existing technology, including
      human interpretability, the ability to leverage structured
      information, generalization capabilities and computational costs.</p>
    <p><b>Thesis Committee:</b><br>
      Artur Dubrawski (Chair)<br>
      Barnabas Poczos<br>
      Russ Salakhutdinov<br>
      Robert A. Stine (Amazon)</p>
    <p>Zoom Meeting link:<a href="https://cmu.zoom.us/s/92165828919?pwd=b0dPUW1jNS9BeDA0NEZBTTBSUGhpQT09" target="_blank"><br>
https://cmu.zoom.us/s/92165828919?pwd=b0dPUW1jNS9BeDA0NEZBTTBSUGhpQT09</a></p>
    <p>Link to Draft Document:<br>
      <a href="https://drive.google.com/file/d/15hE6NapHCOEO0wxgvjLdv6XUhYLxAa3N/view?usp=sharing" target="_blank">https://drive.google.com/file/d/15hE6NapHCOEO0wxgvjLdv6XUhYLxAa3N/view?usp=sharing</a></p>
    <pre cols="72">-- 
Diane Stidle
Graduate Programs Manager
Machine Learning Department
Carnegie Mellon University
<a href="mailto:stidle@andrew.cmu.edu" target="_blank">stidle@andrew.cmu.edu</a></pre>
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