[ABE-L] Seminário PIPGEs com Dylan Molenaar: 08/03 às 14hs no ICMC-USP

[Rafael Izbicki]

Caros,

Na próxima sexta-feira, 08 de março, às 14:00h, reiniciaremos os seminários
do Programa Interinstitucional de Pós-Graduação em Estatística (PIPGEs) da
UFSCar-USP.

Nome: Dylan Molenaar (University of Amsterdam)

Título: Autoencoders for Latent Variable Modeling

Resumo: Latent variable models have many practical uses in modeling
cross-sectional and longitudinal differences in multi-dimensional datasets.
For instance, in psychometrics, latent variable models are used to model
individual differences and account for measurement error in theoretical
constructs like intelligence and personality, and in econometrics, latent
variable models are used to dynamically model econometric measures like
stock wages over time. Estimation of these latent variable models has been
dominated by variations of maximum likelihood estimation, least squares
estimation, and Bayesian estimation. Although for continuous data,
estimation is relatively fast and easily applied to high-dimensional
datasets, for discrete data, estimation is arguably more challenging.
Therefore, recently interest has grown in estimating latent variable models
using neural networks. In this talk, we focus on a specific neural network:
The autoencoder. That is, we study how autoencoders from the field of deep
learning (Goodfellow et al., 2016) can be used to estimate latent variable
models for discrete data from psychometrics in a fast and non-parametric
way. Various challenges are addressed including parameter consistency,
missing data, and robustness in the setup of the encoder.

Local: ICMC- USP São Carlos. Sala 3-102

[image: image.png]

          Rafael

--
Rafael Izbicki
Assistant Professor | Vice Director of Graduate Studies
Department of Statistics
Federal University of São Carlos (UFSCar)
www.rizbicki.ufscar.br
www.small.ufscar.br
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