37 citations · 183 across the 28 of their papers we have counts for
7 papers · 1 filter
First-Order Algorithms Without Lipschitz Gradient: A Sequential Local Optimization Approach
Junyu Zhang, Mingyi Hong
First-order algorithms have been popular for solving convex and non-convex optimization problems. A key assumption for the majority of these algorithms is that the gradient of the…
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
Junyu Zhang, Alec Koppel, Amrit Singh Bedi +2
In recent years, reinforcement learning (RL) systems with general goals beyond a cumulative sum of rewards have gained traction, such as in constrained problems, exploration, and a…
On the Divergence of Decentralized Non-Convex Optimization
Mingyi Hong, Siliang Zeng, Junyu Zhang +1
We study a generic class of decentralized algorithms in which agents jointly optimize the non-convex objective , while only communicating with th…
Generalization Bounds for Stochastic Saddle Point Problems
Junyu Zhang, Mingyi Hong, Mengdi Wang +1
This paper studies the generalization bounds for the empirical saddle point (ESP) solution to stochastic saddle point (SSP) problems. For SSP with Lipschitz continuous and strongly…
Stochastic Variance-Reduced Prox-Linear Algorithms for Nonconvex Composite Optimization
Junyu Zhang, Lin Xiao
We consider minimization of composite functions of the form , where and are convex functions (which can be nonsmooth) and is a smooth vector mapping. In a…
Finite-size analysis of continuous variable source-independent quantum random number generation
Junyu Zhang, Yi-Chen Zhang, Ziyong Zheng +3
We study the impact of finite-size effect on continuous variable source-independent quantum random number generation. The central-limit theorem and maximum likelihood estimation th…