[Seminario] INVITACION SEMINARIO Seminario de Aprendizaje de Máquinas, VIERNES 02 DE DICIEMBRE A LAS 14:00 HRS.

Maria Ines mrivera en dim.uchile.cl
Lun Nov 28 17:33:20 CLST 2016


*Estimados Académicos y Alumnos,
*

*
se les invita para este Viernes 02 de  Diciembre a las 14:30 hrs , al 
**Seminario de Aprendizaje de Máquinas, que tendrá lugar en la sala de  
Seminarios John Von Neumann CMM, de Beauchef 851, Torre Norte Piso 7.
*

*
*

*Seminario de Aprendizaje de Máquinas
*

*Expositor
*

Karim Pichara
  PUC

*Título
*Variational Inference


*Abstract: *Bayesian methods have shown to be very successful and 
attractive approaches in Machine Learning, thanks to the natural 
representation of uncertainty in real problems, the automatic control of 
overfitting, and the intuitive modeling of semantics through the use of 
latent variables and graphical models. In most cases, Bayesian 
approaches have to deal with the inference of posterior probabilities of 
latent variables given data, in order to make predictions for future 
cases or to perform model selection as well. Unfortunately, in most of 
the real cases, the estimation of those posteriors is intractable, 
forcing us to use approximate inference methods. In this talk, we will 
learn about Variational Inference, a very powerful tool that cast 
posterior approximations as an optimization problem, where simpler 
families of distributions are used to approximate true posteriors 
through the optimization of a lower bound on the marginal likelihood. We 
will explore the basics on Variational Inference, we will see some real 
applications, what are the main limitations today, and what is the focus 
of future research in this field.

*Cuándo:* 2/12/16, 1430hrs

*Dónde: *Sala John von Neumann, CMM (Beauchef 851, torre norte, piso 7).

Esperando contar con su presencia, les saluda,

Ma. Inés Rivera



-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://listas.dim.uchile.cl/pipermail/seminario/attachments/20161128/b34ac66c/attachment.html>


Más información sobre la lista de distribución Seminario