Dear Colleagues,
We would like to invite you to the following SPASS seminar, jointly organized by UniPi, SNS, UniFi and UniSi (abstract below):
*Scalable large scale variational inference * by *Omiros Papaspiliopoulos* (Università Bocconi)
The seminar will take place on *TUE, 15.10.2024* at *14:00 CET *in Aula Seminari, Dipartimento di Matematica, UNIPI and streamed online at this link https://meet.google.com/gji-phwo-vbg.
The organizers, A. Agazzi, G. Bet, A. Caraceni, F. Grotto, G. Zanco https://sites.google.com/unipi.it/spass https://www.google.com/url?q=https://sites.google.com/unipi.it/spass&source=gmail-imap&ust=1665669490000000&usg=AOvVaw07o0tKOUGmZjDDF2Ta7pQY
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*Title: Scalable large scale variational inference *
*Abstract: The motivation behind this work is a computational framework for approximate statistical inference for the broad class of generalized bi-linear mixed models, special cases of which are generalized linear mixed models, factor models and probabilistic factorization models to mention a few popular examples. The objective is that the resultant inference has theoretically provable guarantees in terms of both uncertainty quantification and computational complexity. * * In this talk, I will first give some highlights of our work in using this framework for analyzing political ideology in Europe and then I will give a stand-alone short introduction to variational inference, discussing some theoretical aspects of its scalability.*