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<div dir="ltr"><b>From:</b> Insper - Seminários Acadêmicos <seminariosacademicos@insper.edu.br><br>
<b>Date:</b> August 24, 2023 at 5:45:37 AM MST<br>
<b>To:</b> Insper - Seminários Acadêmicos <seminariosacademicos@insper.edu.br><br>
<b>Subject:</b> <b>Academic Seminar of Data Science with Mariana Rodrigues Motta of Unicamp - Online</b><br>
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<p class="MsoNormal" align="center" style="text-align:center;line-height:115%"><b><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">Title: </span></b><span lang="EN-US" style="font-family:"Verdana",sans-serif">Unsupervised
Bayesian Classification for Mixed Regression Models with Scalar and Functional Covariates<o:p></o:p></span></p>
<p class="MsoNormal" align="center" style="text-align:center;line-height:115%"><span lang="EN-US" style="font-size:8.0pt;line-height:115%;font-family:"Verdana",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal" align="center" style="text-align:center;line-height:115%"><span lang="EN-US" style="font-size:8.0pt;line-height:115%;font-family:"Verdana",sans-serif">Joint work with Nancy L. Garcia, Helio Migon, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden,
Julio O. Giodano and Martin Matias Perez</span><span lang="EN-US" style="font-size:8.0pt;line-height:115%;font-family:"Verdana",sans-serif;mso-fareast-language:PT-BR"><o:p></o:p></span></p>
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<b><span style="font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">Speaker:</span></b><span style="font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">
<a href="https://www.ime.unicamp.br/~marianar/">Mariana Rodrigues Motta</a> <o:p>
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<b><span style="font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">University:</span></b><span style="font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">
<a href="https://www.unicamp.br/unicamp/universidade">Unicamp</a><o:p></o:p></span></p>
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<b><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:#414042;mso-fareast-language:PT-BR"><o:p> </o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify;line-height:115%"><b><span lang="EN-US" style="font-family:"Verdana",sans-serif;mso-fareast-language:PT-BR">Abstract:</span></b><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:#414042;mso-fareast-language:PT-BR"> </span><span lang="EN-US" style="font-family:"Verdana",sans-serif;mso-fareast-language:PT-BR">
</span><span lang="EN-US" style="font-family:"Verdana",sans-serif">We perform unsupervised classification of a scalar response by considering a mixture model based on parametric distributions. Our goal in this work is to model the mixture probabilities by means
of a generalized linear model with functional and scalar covariates. The model accounts for more than one functional covariate defined in different supports. Linear/Non linear functions of the functional covariates are expanded using B-splines to reduce the
dimensionality of the problem. A Bayesian approach is considered for estimating the parameters and providing predictions of the latent classification vector. The Bayesian approach considers the classical Markov Chain Monte Carlo estimation method as well as
a new method called Variational Bayes method, which is an optimization procedure to approximate the posterior distribution. The method is motivated by two data examples that are not easily handled by existing methods. The first example concerns a normal mixture
model and the other a zero inflated mixture of Poisson distributions.</span><span lang="EN-US" style="font-family:"Verdana",sans-serif;mso-fareast-language:PT-BR"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">August 31, 2023</span><span style="mso-fareast-language:PT-BR"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">12pm São Paulo, Brasil (UTC/GMT -03:00)</span><span style="mso-fareast-language:PT-BR"><o:p></o:p></span></p>
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<p class="MsoNormal"><span lang="EN-US" style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR">The seminar will be streamed at the
</span><span style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR"><a href="https://zoom.us/j/95781336030"><span lang="EN-US">link</span></a></span><span lang="EN-US" style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black;mso-fareast-language:PT-BR"><o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-size:8.5pt;font-family:"Verdana",sans-serif;color:#3A3A41;mso-fareast-language:PT-BR">Rua Quatá, 300 - Vila Olímpia - São Paulo/SP - Brasil - CEP: 04546-042 | Tel: (11) 4504-2400</span><o:p></o:p></p>
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