Carissimi colleghi, scusandomi per eventuali invii multipli, vi inoltro il seguente annuncio di seminario.
Tutti gli interessati sono invitati a partecipare.
Cordialmente, Enea Bongiorno
-------------------------------- - data e orario: 23 maggio 2024 ore 15.00 - aula 204, campus Perrone, via Perrone, 18, Novara. Università del Piemonte Orientale. - on-line: meet.google.com/iap-gjcr-bkb
Title: *Regression analysis with density functions in Bayes spaces* *Ivana Pavlů*, Palacký University Olomouc, Czech Republic
*Abstract*: Regression analysis offers tools for explaining the relation between (a set of) dependent and independent variables. Recent advances extend the available response types from uni- or multivariate to functional, and more recently also distributional responses. For functional distributions, often represented through probability density functions, the Bayes space framework was developed to respect the relative information they carry. The Hilbert space structure of Bayes space enables one to utilize standard methods of functional data analysis for the use on - properly transformed - density functions. Focusing on regression analysis, it is possible to construct adequate models with densities on the side of both the dependent and independent variables.
In this seminar, a brief overview of regression models for univariate densities will be presented. A closer attention will be given to the possible generalization of additive regression model for bivariate distributions. Finally, an outlook at the Bayesian inference in linear regression with probability densities will be discussed. All proposed methods will be demonstrated on real data from the fields of geochemistry and demographics.
----------------------------------- Locandina dell'evento https://drive.google.com/file/d/1AW4P1_HNdVO7Ot70mjM-KCQLhnSSVmRi/view?usp=sharing Seminari Matematici Statistici https://seminari-ms.uniupo.it/home-page -----------------------------------
Dear all,
Domenico Marinucci's seminar will take place on Monday 27th May and not on the 29th as mistakenly stated in the previous message. I apologise for the error.
Speaker : Domenico Marinucci (https://sites.google.com/view/domenicomarinucci/home) Affiliation: Dipartimento di Matematica - Università Roma Tor Vergata Title: Spectral complexity of deep neural networks Date: Monday, May 27, 2024 at 11.30 Place: Aula 704 (7th floor) , Dipartimento di Matematica at University of Genova, Via Dodencaneso 35,
Abstract: It is well-known that randomly initialized, push-forward, fully-connected neural networks weakly converge to isotropic Gaussian processes, in the limit where the width of all layers goes to infinity. In this paper, we propose to use the angular power spectrum of the limiting fields to characterize the complexity of the network architecture. In particular, we define sequences of random variables associated with the angular power spectrum, and provide a full characterization of the network complexity in terms of the asymptotic distribution of these sequences as the depth diverges. On this basis, we classify neural networks as low-disorder, sparse, or high-disorder; we show how this classification highlights a number of distinct features for standard activation functions, and in particular, sparsity properties of ReLU networks. Our theoretical results are also validated by numerical simulations.
Joint work with Simmaco Di Lillo, Michele Salvi e Stefano Vigogna
Best wishes,
Ernesto
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Enea Bongiorno -
Ernesto De Vito