The Institute for Statistics and Mathematics is pleased to invite you to the next research seminar, taking place on campus:

Tatyana Krivobokova (Department of Statistics and Operations Research, University of Vienna)
Iterative Regularisation in Ill-Posed Generalised Linear Models
Friday, May 3, 2024, 10:30 am, Building D4, Room D4.0.127

Abstract:
We study the problem of regularized maximum-likelihood optimization in ill-posed generalized linear models with covariates that include subsets that are relevant and that are irrelevant for the response. It is assumed that the source of ill-posedness is a joint low dimensionality of the response and a subset of the relevant covariates in the sense of a latent factor generalized linear model (GLM). In particular, we propose a novel iteratively-reweighted- partial-least-squares (IRPLS) algorithm and show that it is better than any other projection or penalization-based regularisation algorithm. Under regularity assumptions on the latent factor GLM we show that the convergence rate of the IRPLS estimator with high probability is the same as that of the maximum likelihood estimator in our latent factor GLM, which is an oracle achieving an optimal parametric rate. Our findings are confirmed by numerical studies. This is a joint work with Gianluca Finocchio.

We aim to stream all on-campus talks via Zoom. A direct link to the stream will be posted on our website.

For further information and the seminar schedule, please see:
www.wu.ac.at/en/statmath/research/resseminar