Model selection and singularities in PPCA and FA models

Datum

22.10.2026

Zeit

15:00 - 16:00

Sprecher

Daniel Windisch

Zugehörigkeit

KU Leuven

Sprache

en

Hauptthema

Biologie

Host

CSBD Math Seminar

Beschreibung

Probabilistic principal component analysis (PPCA) and factor analysis (FA) are methods for understanding the principal directions along which given data is distributed. Both classes of models have been used extensively in various fields such as psychology and sociology, and for applications including classification problems. This talk will present an effective model-selection method for PPCA and FA and, in particular, for determining the effective dimension of a noisy data set. The main technique is based on resolution of singularities for real schemes arising from these models. This is joint work with Mathias Drton and Andrew McCormack.

Letztmalig verändert: 20.10.2026, 07:40:01