[ABE-L] Hoje: Hedibert Lopes no IMPA

[Roberto Imbuzeiro Moraes Felinto de Oliveira]

>
> Título: Bayesian learning in high-dimensional state-space models
> Expositor: Hedibert Lopes (INSPER, São Paulo)
> Data: Quarta-feira, 17 de abril de 2019, 15:30
> Local: IMPA, Sala 228
> Resumo: Applied Bayesian Statistics has benefited greatly from the
> avalanche of Monte Carlo-based tools for approximate posterior
> inference in highly complex and structured scientific models. From
> environmental and health studies to financial applications, virtually
> all areas of science where evidence-based scrutiny is mandatory to
> validate scientific hypotheses have benefitted from such technological
> explosion.
>
> My research also exemplifies these trends. I will discuss work on
> high-dimensional state-space models with particular attention to
> time-varying covariance learning. In one direction, my co-authors and
> I deal with the curse of dimensionality via parameter reduction, such
> as those found in the factor modelling literature. In another
> direction, we heavily regularize the estimation of parameters. I will
> review the challenges we faced when dealing with such high-dimensional
> state-space models. Two or three motivating examples from my recent
> research will be used throughout the talk. I finish with a few
> directions of my future research in these and related areas.
>

-- 
Roberto Imbuzeiro Oliveira
Professor, IMPA
rimfo em impa.br, rob.oliv em gmail.com
sites.google.com/view/roboliv
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