1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.OC2024
Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence
Ilyas Fatkhullin, Niao He
This paper revisits the convergence of Stochastic Mirror Descent (SMD) in the contemporary nonconvex optimization setting. Existing results for batch-free nonconvex SMD restrict th…
cs.LG2023
Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
Anas Barakat, Ilyas Fatkhullin, Niao He
We consider the reinforcement learning (RL) problem with general utilities which consists in maximizing a function of the state-action occupancy measure. Beyond the standard cumula…
math.OC2023★ 1 cited
Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods
Junchi Yang, Xiang Li, Ilyas Fatkhullin +1
The classical analysis of Stochastic Gradient Descent (SGD) with polynomially decaying stepsize relies on well-tuned depending on problem parameters such as…