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math.OC2026
Lower Bounds for Anytime Acceleration of Gradient Descent
Chung-En Tsai, Ilyas Fatkhullin, Liang Zhang +1
Recent work suggests that the convergence rate of gradient descent (GD) in smooth convex optimization can be significantly improved by employing large stepsizes that may violate th…
cs.LG2026
Global Optimality for Constrained Exploration via Penalty Regularization
Florian Wolf, Ilyas Fatkhullin, Niao He
Efficient exploration is a central problem in reinforcement learning and is often formalized as maximizing the entropy of the state-action occupancy measure. While unconstrained ma…