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stat.ML2023
FEMDA: a unified framework for discriminant analysis
Pierre Houdouin, Matthieu Jonckheere, Frederic Pascal
Although linear and quadratic discriminant analysis are widely recognized classical methods, they can encounter significant challenges when dealing with non-Gaussian distributions…
cs.LG2023
Policy Optimization via Adv2: Adversarial Learning on Advantage Functions
Matthieu Jonckheere, Chiara Mignacco, Gilles Stoltz
We revisit the reduction of learning in adversarial Markov decision processes [MDPs] to adversarial learning based on --values; this reduction has been considered in a number of…