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1st Gerhart Bruckmann Lecture in Statistics and Data Science

Oct 3rd:

Univ.-Prof. Dr. Tatyana Krivobokova, Institut für Statistik und Operations Research, Universität Wien, Österreich: An extended latent factor framework for ill-posed generalised linear regression

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Meeting-ID: 280 519 2121
Passwort: 584190

Abstract:

The classical latent factor model for (generalised) ill-posed linear regression is extended by assuming that, up to an unknown orthogonal transformation, the features consist of subsets that are relevant and irrelevant to the response. Furthermore, a joint low-dimensionality is imposed only on the relevant features and the response variable. This framework not only allows for a comprehensive study of the partial-least-squares (PLS) algorithm under random design, but also sheds light on the performance of other regularisation methods that exploit sparsity or unsupervised projection. Moreover, we propose a novel iteratively-reweighted-partial-least-squares (IRPLS) algorithm for ill-posed generalised linear models and obtain its convergence rates working in the suggested framework. This is a joint work with Gianluca Finocchio.

Event

Time & date

October 03, 2024

15:30 - 17:00 PM

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Location

S2 Z74, Science Park 2

Contact

alexandra.stadler@jku.at