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The Center for Intelligent Systems (CIS) at EPFL, a joint initiative of the schools ENAC, IC, SB, STI and SV seeks to advance research and practice in the strategic field of intelligent systems.
RIKEN is Japan's largest comprehensive research institution renowned for high-quality research in a diverse range of scientific disciplines.
RIKEN Center for Advanced Intelligence Project (AIP) houses more than 30 research teams ranging from fundamentals of machine learning and optimization, applications in medicine, materials, and disaster, to analysis of ethics and social impact of artificial intelligence.
【The 16th Seminar】
Date and Time: July 13th 5:00pm – 6:00pm(JST)
Speaker: Minh Ha Quang, RIKEN AIP
Title: Regularized information geometric and optimal transport distances between covariance operators and Gaussian processes
Information geometry (IG) and Optimal transport (OT) have been attracting much research attention in various fields, in particular machine learning and statistics. In this talk, we present results on the generalization of IG and OT distances for finite-dimensional Gaussian measures to the setting of infinite-dimensional Gaussian measures and Gaussian processes.Our focus is on the Entropic Regularization of the 2-Wasserstein distance and the generalization of the Fisher-Rao distance and related quantities.In both settings, regularization leads to many desirable theoretical properties, including in particular dimension-independent convergence and sample complexity. All of the presented formulations admit closed form expressions that can be efficiently computed and applied practically.
Minh Ha Quang is currently a unit leader at RIKEN AIP where he leads the Functional Analytic Learning Unit. He received the PhD degree in Mathematics from Brown University (RI, USA). Before joining AIP, he was a researcher at the Italian Institute of Technology in Genova, Italy. His current research focuses on functional analytic and geometrical methods in machine learning and statistics.
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