[ABE-L] Seminários PPGEst UFRGS 2024/03 - Rafael Izbicki

[Guilherme Pumi]

Prezados.

É com imenso prazer que divulgamos o próximo seminário do ciclo 2024/03 do
PPGEst.

O seminário ocorrerá de forma remota nesta terça feira, *10/12 às 13:30*
pela plataforma mconf do programa:

https://mconf.ufrgs.br/webconf/ppgest

Mais detalhes abaixo:

*Palestrante*: Prof. Dr.  Rafael Izbicki (UFSCAR)

*Título*: Local Prediction Sets With Applications to Statistical Inference

*Abstract*:  Quantifying uncertainty is essential for reliable predictive
modeling and statistical inference. Traditional conformal methods ensure
marginally valid prediction intervals but often lack adaptability and fail
to achieve conditional coverage. We introduce a model-agnostic approach
leveraging regression trees and Random Forests to construct data-adaptive
partitions that approximate local coverage guarantees, enhancing
scalability and accuracy of existing approaches. Extending this idea to
statistical inference, we propose novel techniques for calibrating
confidence sets with finite-sample and asymptotic conditional coverage.
These methods rely on simulated data for calibration, making them effective
even in small-sample regimes or when nuisance parameters are present.
Experiments show these techniques outperform existing approaches, offering
practical tools for uncertainty quantification in complex settings.

Com moderação do Prof. Dr. Flávio Augusto Ziegelmann.


Att.
Guilherme Pumi
Professor Associado do Departamento de Estatística - UFRGS
Coordenador do Programa de Pós-Graduação em Estatística - PPGEst
http://lattes.cnpq.br/0541756341423245
https://orcid.org/0000-0002-6256-3170
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