Dear all, On Thursday, 7th May, at 12:00 in room A307b, the Department of AI, Data and Decision Sciences of Luiss University of Rome will host a seminar by Petros Dellaportas (University College London) Title: “Gaussian Invariant Markov Chain Monte Carlo” Abstract: We develop sampling methods, which consist of Gaussian invariant versions of random walk Metropolis (RWM), Metropolis adjusted Langevin algorithm (MALA) and second-order Hessian or Manifold MALA. Unlike standard RWM and MALA we show that Gaussian invariant sampling can lead to ergodic estimators with significantly improved statistical efficiency. This is due to a remarkable property of Gaussian invariance that allows us to obtain exact analytical solutions to the Poisson equation for Gaussian targets. These solutions can be used to construct efficient and easy-to-use control variates for variance reduction of estimators under any intractable target. We demonstrate the new samplers and estimators in several examples, including high-dimensional targets in latent Gaussian models, where we compare against several advanced methods and obtain state-of-the-art results. We also provide theoretical results regarding geometric ergodicity and an optimal scaling analysis that shows the dependence of the optimal acceptance rate on the Gaussianity of the target. 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