Agenda

19 Mar 2024 12:15

Penalized mixed-effects multitask learning: a framework for regularizing multilevel models

Aula Delta 2C, Edificio DELTA - Campus Scientifico via Torino and Zoom

Speaker: Andrea Cappozzo, Università degli Studi di Milano

Titolo: Penalized mixed-effects multitask learning: a framework for regularizing multilevel models with applications on DNA methylation biomarkers creation

Zoom Link: https://unive.zoom.us/j/85153268624?pwd=MzBhdlA2M1B2dThJQ2Y5T0EwUE5PZz09

Abstract:
Linear mixed modeling is a well-established technique widely employed when observations possess a grouping structure. Nevertheless, this standard methodology is no longer applicable when the learning framework encompasses a multivariate response and high-dimensional predictors. To overcome these issues, a penalized estimation scheme based on an expectation-maximization (EM) algorithm is proposed, in which any penalty criteria previously devised for fixed-effects models can be conveniently incorporated into the fitting process. We employ the novel methodology for creating surrogate biomarkers of cardiovascular risk factors, such as lipids and blood pressure, from whole-genome DNA methylation data in a multi-center study. The proposed approach shows promising results in both predictive accuracy and bio-molecular interpretation compared to state-of-the-art alternatives.

Based on joint work with Francesca Ieva and Giovanni Fiorito.

Bio Sketch:
Andrea Capozzo is currently Assistant Professor (RTDB) at the Department of Economics, Management, and Quantitative Methods of University of Milan. His methodological interests are related to the domain of applied statistics and statistical learning, with particular focus on mixture modeling.

Lingua

L'evento si terrà in inglese

Organizzatore

Dipartimento di Scienze Ambientali, Informatica e Statistica - Gruppo Statistica (Prosdocimi)

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