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<p style="margin-top:0;margin-bottom:0"><font face="Calibri, sans-serif">********REMINDER**********REMINDER******MONDAY, APRIL 22 at 11:00AM************</font></p>
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<p style="margin-top:0; margin-bottom:0">& GFDI COLLOQUIUM &</p>
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<p class="x_x_MsoNormal" style="text-align:center" align="center"><b style=""><span style="font-size:24.0pt; color:red">Title</span></b></p>
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<p class="x_x_MsoPlainText" style="text-align:center" align="center"><b style=""><span style="font-size:20.0pt; font-family:"Times New Roman",serif; color:#1A0886">“</span></b><b style=""><span style="font-size:20.0pt; color:#1A0886">Discovery mathematical
models from experimental data</span></b><b style=""><span style="font-size:20.0pt; font-family:"Times New Roman",serif; color:#1A0886">"</span></b></p>
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<p class="x_x_MsoNormal" style="text-align:center" align="center"><b style=""><span style="font-size:24.0pt; font-family:"BernhardMod BT",serif; color:red">Speaker</span></b></p>
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<p class="x_x_MsoPlainText" style="text-align:center" align="center"><b style=""><span style="font-size:18.0pt; font-family:"Arial Rounded MT Bold",sans-serif; color:#14038F">Dr. Alessandro Alla</span></b></p>
<p class="x_x_MsoPlainText" style="text-align:center" align="center"><span style="font-size:18.0pt; font-family:"Arial Rounded MT Bold",sans-serif; color:#14038F">Department of Mathematics</span></p>
<p class="x_x_MsoPlainText" style="text-align:center" align="center"><span style="font-size:18.0pt; font-family:"Arial Rounded MT Bold",sans-serif; color:#14038F">PUC-Rio, Brazil
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<p class="x_x_MsoNormal" style="text-align:center" align="center"><b style=""><span style="font-size:20.0pt; font-family:"BernhardMod BT",serif; color:red">Time and Place</span></b></p>
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<p class="x_x_MsoNormal" style="text-align:center" align="center"><b style=""><span style="font-size:18.0pt; font-family:"BernhardMod BT",serif; color:#1B0284">11:00AM</span></b><b style=""><span style="font-size:18.0pt; color:#1B0284">, Monday, April 22, 2019</span></b></p>
<p class="x_x_MsoNormal" style="text-align:center" align="center"><b style=""><span style="font-size:18.0pt; font-family:"BernhardMod BT",serif; color:#1B0284">Melvin Stern Seminar/Reading Room</span></b></p>
<p class="x_x_MsoNormal" style="text-align:center" align="center"><b style=""><span style="font-size:18.0pt; font-family:"BernhardMod BT",serif; color:#1B0284">18 Keen Building</span></b></p>
<p class="x_x_MsoNormal" style="text-align:center" align="center"><b style=""><span style="font-size:18.0pt; font-family:"BernhardMod BT",serif; color:#0066FF">Refreshments will be served at 10:30AM</span></b></p>
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<p class="x_x_MsoPlainText"><span style="font-size:12.0pt; font-family:"Times New Roman",serif">ABSTRACT: In this talk, we will present two recent techniques to discover mathematical models from data using machine learning techniques. In the first part of the
talk, we advocate the use of Dynamic Mode Decomposition (DMD), an equation-free method, to approximate the data with a linear model. DMD is a spatio-temporal matrix decomposition of a data matrix that correlates spatial features while simultaneously associating
the activity with periodic temporal behavior. With this decomposition, one can obtain a reduced dimensional surrogate model and use for future state predictions or extrapolate missing information from the data. In the second part, we address the problem of
discovering nonlinear ODEs and PDEs from data. We will show that we can recover the mathematical problem by means of sparse optimization methods such as LASSO and RIDGE regression. Examples and applications of the methods will be showed during the talk.</span></p>
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