1 citations · 1 across the 8 of their papers we have counts for
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Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization
Yufeng Yang, Erin Tripp, Yifan Sun +2
Recent studies have shown that many nonconvex machine learning problems satisfy a generalized-smooth condition that extends beyond traditional smooth nonconvex optimization. Howeve…
Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation
Yudan Wang, Yue Wang, Yi Zhou +1
Actor-critic (AC) is a powerful method for learning an optimal policy in reinforcement learning, where the critic uses algorithms, e.g., temporal difference (TD) learning with func…
Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance
Qi Zhang, Yi Zhou, Shaofeng Zou
This paper provides the first tight convergence analyses for RMSProp and Adam in non-convex optimization under the most relaxed assumptions of coordinate-wise generalized smoothnes…
Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Ashley Prater-Bennette +2
Distributionally robust optimization (DRO) is a powerful framework for training robust models against data distribution shifts. This paper focuses on constrained DRO, which has an…