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<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Welcome to the IDA Machine Learning Seminar on Wednesday, May 19, 15:15<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Yura Malitsky,
</span></b><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Linköping University<b><o:p></o:p></b></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Adaptive gradient descent without descent<o:p></o:p></span></b></p>
<p class="MsoNormal"><i><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Abstract:</span></i><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">
</span></b><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">In this talk I will present some recent results for the most classical optimization method - gradient descent. We will show that a simple zero cost rule is sufficient to
completely automate gradient descent. The method adapts to the local geometry, with convergence guarantees depending only on the smoothness in a neighborhood of a solution. The presentation is based on a joint work with K. Mishchenko, see
<a href="https://arxiv.org/abs/1910.09529">https://arxiv.org/abs/1910.09529</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><i><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Zoom link:</span></i><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">
<a href="https://liu-se.zoom.us/j/69011766298">https://liu-se.zoom.us/j/69011766298</a><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-bottom:12.0pt"><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal" style="margin-bottom:12.0pt"><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">-------<br>
The list of future seminars in the series is available at </span><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif"><a href="http://www.ida.liu.se/research/machinelearning/seminars/"><span lang="EN-US">http://www.ida.liu.se/research/machinelearning/seminars/</span></a></span><span lang="EN-US" style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Welcome!<br>
IDA Machine Learning Group<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Segoe UI",sans-serif">Linköping University<o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-US"><o:p> </o:p></span></p>
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