<div dir="ltr"><div class="gmail_default" style="font-family:verdana,sans-serif">Fantástica notícia, Dani. </div><div class="gmail_default" style="font-family:verdana,sans-serif"><br></div><div class="gmail_default" style="font-family:verdana,sans-serif">Haveria alguma chance de organizar transmissão da conferência dele via web?</div><div class="gmail_default" style="font-family:verdana,sans-serif"><br></div><div class="gmail_default" style="font-family:verdana,sans-serif">Abs, Pedro</div></div><br><div class="gmail_quote"><div dir="ltr">Em qua, 13 de jun de 2018 às 20:07, Dani Gamerman <<a href="mailto:dani@im.ufrj.br">dani@im.ufrj.br</a>> escreveu:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><br>
Caros colegas <br>
<br>
É com prazer que anunciamos a visita do Prof. Michael Jordan, <br>
da Universidade da California (Berkeley) à UFRJ. Essa visita <br>
está sendo conjuntamente organizada pelos Programa de PG em <br>
Estatística, Informática e Engenharia de Sistemas e Computação.<br>
<br>
A visita será no dia 07 de agosto de 2018 e consistirá em<br>
11-12 conferência no auditório do CT2<br>
12-13 almoço<br>
13-14 pequenas reuniões com alunos e docentes<br>
<br>
Pedimos que os interessados em terem reunião com o Prof. Jordan<br>
nos informem do seu interesse e procuraremos acomoda-los da melhor<br>
forma possível.<br>
<br>
Título e resumo da palestra seguem abaixo<br>
On Computational Thinking, Inferential Thinking and Data Science<br>
<br>
The rapid growth in the size and scope of datasets in science and<br>
technology has created a need for novel foundational perspectives <br>
on data analysis that blend the inferential and computational sciences. <br>
That classical perspectives from these fields are not adequate to <br>
address emerging problems in Data Science is apparent from their <br>
sharply divergent nature at an elementary level---in computer science, <br>
the growth of the number of data points is a source of "complexity" <br>
that must be tamed via algorithms or hardware, whereas in statistics, <br>
the growth of the number of data points is a source of "simplicity" <br>
in that inferences are generally stronger and asymptotic results can <br>
be invoked. On a formal level, the gap is made evident by the lack <br>
of a role for computational concepts such as "runtime" in core <br>
statistical theory and the lack of a role for statistical concepts <br>
such as "risk" in core computational theory. I present several research<br>
vignettes aimed at bridging computation and statistics, discussing <br>
the problem of inference under privacy and communication constraints,<br>
the problem of the control of error rates in multiple decision-<br>
making, and the notion of the "optimal way to optimize".<br>
<br>
<br>
Um pequeno resumo do CV do Prof. Jordan segue abaixo.<br>
Michael I. Jordan is the Pehong Chen Distinguished Professor in the<br>
Department of Electrical Engineering and Computer Science and the<br>
Department of Statistics at the University of California, Berkeley.<br>
His research interests bridge the computational, statistical, cognitive<br>
and biological sciences. Prof. Jordan is a member of the National <br>
Academy of Sciences and a member of the National Academy of Engineering.<br>
He has been named a Neyman Lecturer and a Medallion Lecturer by the<br>
Institute of Mathematical Statistics. He received the IJCAI Research<br>
Excellence Award in 2016, the David E. Rumelhart Prize in 2015 and<br>
the ACM/AAAI Allen Newell Award in 2009.<br>
<br>
Esses dados já estão disponíveis na lista de palestras do Programa <br>
de PG em Estatística (<a href="http://www.dme.ufrj.br" rel="noreferrer" target="_blank">www.dme.ufrj.br</a>), na aba palestras do 2018/2.<br>
<br>
Agradeço a colaboração dos Profs. Daniel Sadoc (Informática) e Daniel<br>
Figueiredo (Engenharia de Sistemas e Computação) na organização.<br>
Agradecemos a divulgação junto a possíveis interessados.<br>
<br>
Saudações acadêmicas<br>
Dani<br>
<br>
*************************************************<br>
Dani Gamerman<br>
Depto. de Métodos Estatísticos (DME)<br>
Lab. de Sistemas Estocásticos (LSE)<br>
Instituto de Matemática - UFRJ<br>
<a href="http://www.dme.ufrj.br/dani" rel="noreferrer" target="_blank">http://www.dme.ufrj.br/dani</a><br>
<a href="http://www.statpop.com.br" rel="noreferrer" target="_blank">www.statpop.com.br</a><br>
fb: StatPop, twitter: @blogStatPop<br>
*************************************************<br>
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</blockquote></div><br clear="all"><div><br></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="verdana, sans-serif">Pedro Luis do Nascimento Silva</font><div><font face="verdana, sans-serif">IBGE - Escola Nacional de Ciências Estatísticas</font></div><div><font face="verdana, sans-serif">IBGE - National School of Statistical Sciences<br>Phone: +55 21 21424957</font></div></div></div></div></div></div></div></div></div>