Dear all, On Wednesday, 15th April, at 12:00 in room A307b, the Department of AI, Data and Decision Sciences of Luiss University of Rome will host a seminar by Gregor Kastner (University of Klagenfurt) Title: "Bayesian nonparametric priors for model-based (partial) clustering” Abstract: We discuss variations of prior distributions for finite and potentially infinite mixture models. First, we extend standard Bayesian nonparametric spatial priors to additionally incorporate the temporal dimension, thereby allowing for spatio-temporal clustering. Second, we show how these priors can be modified to cater for partial effects by a priori distinguishing between control and target variables. Third, we propose a novel prior for modelling the weights in mixture models. It is based on the Selberg Dirichlet distribution, an extension of the standard Dirichlet with a repulsive term, and penalises mixture weights that lie close to each other. The approaches are illustrated with applications from various fields: modelling unemployment, quantifying the effect of European agricultural subsidies, and uncovering patterns in biomedical data. Anyone interested in attending is welcome; just email me for logistical purposes. Hoping to meet you there! Best, Matteo Iacopini La presente e-mail proviene da Luiss Guido Carli e s'intende inviata per scopi lavorativi. Tutte le informazioni ivi contenute, compresi eventuali allegati, sono da ritenersi esclusivamente confidenziali e riservati secondo i termini del vigente D.Lgs. 196/2003 in materia di privacy e del Regolamento europeo 679/2016 - GDPR. È vietato qualsiasi ulteriore utilizzo non autorizzato. Qualora la stessa Le fosse pervenuta per errore, La preghiamo di eliminarla immediatamente e di darcene tempestiva comunicazione. Grazie. This e-mail message is sent by Luiss Guido Carli for business purposes. All informations contained therein, including any attachments, are for the sole use of the intended recipient and may contain confidential and privileged information pursuant to Legislative Decree 196/2003 and the European General Data Protection Regulation 679/2016 - GDPR -. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by soon reply this e-mail and destroy all copies of the original message. Thanks