Web: http://arxiv.org/abs/2205.03078

May 9, 2022, 1:11 a.m. | Christian Soize

cs.LG updates on arXiv.org arxiv.org

This paper deals with the taking into account a given set of realizations as
constraints in the Kullback-Leibler minimum principle, which is used as a
probabilistic learning algorithm. This permits the effective integration of
data into predictive models. We consider the probabilistic learning of a random
vector that is made up of either a quantity of interest (unsupervised case) or
the couple of the quantity of interest and a control parameter (supervised
case). A training set of independent realizations of …

arxiv learning ml probability

More from arxiv.org / cs.LG updates on arXiv.org

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC