[ABE-L] visita do Prof. Michael Jordan à UFRJ

[Basilio de Braganca Pereira]

Dani 
Estou dentro. Sugeri aos organizadores do Sinape trazê-lo mas era preciso 2 anos de antecedência. Parabens a quem conseguiu trazê-lo
Basilio

Enviado do meu iPhone

Em 13 de jun de 2018, à(s) 20:06, Dani Gamerman <dani em im.ufrj.br> escreveu:

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