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cs.LG2025
On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
Yang Cai, Gabriele Farina, Julien Grand-Clément +4
Non-ergodic convergence of learning dynamics in games is widely studied recently because of its importance in both theory and practice. Recent work (Cai et al., 2024) showed that a…
cs.LG2024
Risk-averse Total-reward MDPs with ERM and EVaR
Xihong Su, Julien Grand-Clément, Marek Petrik
Optimizing risk-averse objectives in discounted MDPs is challenging because most models do not admit direct dynamic programming equations and require complex history-dependent poli…