Skip To Main Content
Pierre Ménard on Muck Rack

Pierre Ménard

As seen in: arXiv, Taylor & Francis Online, ABC Digital, Economie Matin, Revue Banque, Decideo (France)
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Pierre

Contact Pierre, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Computer Science > Machine Learning

|
By Pierre Ménard, Remi Munos, Omar Darwiche Domingues
| arXiv
We propose SmoothCruiser, a new planning algorithm for estimating the value function in entropy-regularized Markov decision processes and two-player games, given a generative model of the environment.
Open in Who Shared Issue with article?

Computer Science > Machine Learning

|
By Pierre Ménard, Tadashi Kozuno, Michal Valko
| arXiv
Open in Who Shared Issue with article?

Computer Science > Machine Learning

|
By Pierre Ménard, Tadashi Kozuno, Michal Valko
| arXiv
We study the problem of learning minimax policies in zero-sum matrix games. Fiegel et al. (2025) recently showed that achieving last-iterate convergence in this setting is harder when the players are uncoupled, by proving a lower bound on the exploitability gap of Omega(t^{-1/4}).
Open in Who Shared Issue with article?
See all 17 articles