1 citations · 4 across the 10 of their papers we have counts for
10 papers
Projection-Free Bandit Online Optimization for Multi-Agent Systems with Dynamic Regret
Xia Jiang, Lu Liu, Gang Feng
This paper investigates distributed online optimization for multi-agent dynamical systems with constrained inputs and time-varying cost functions. While online convex optimization…
Empirical Bayesian Multi-Bandit Learning
Xia Jiang, Rong J. B. Zhu
Multi-task learning in contextual bandits has attracted significant research interest due to its potential to enhance decision-making across multiple related tasks by leveraging sh…
Efficient Single-Loop Stochastic Algorithms for Nonconvex-Concave Minimax Optimization
Xia Jiang, Linglingzhi Zhu, Taoli Zheng +1
Nonconvex-concave (NC-C) finite-sum minimax problems have wide applications in signal processing and machine learning tasks. Conventional stochastic gradient algorithms, which rely…
Shuffling Gradient Descent-Ascent with Variance Reduction for Nonconvex-Strongly Concave Smooth Minimax Problems
Xia Jiang, Linglingzhi Zhu, Anthony Man-Cho So +2
In recent years, there has been considerable interest in designing stochastic first-order algorithms to tackle finite-sum smooth minimax problems. To obtain the gradient estimates,…
Distributed stochastic projection-free solver for constrained optimization
Xia Jiang, Xianlin Zeng, Lihua Xie +2
This paper proposes a distributed stochastic projection-free algorithm for large-scale constrained finite-sum optimization whose constraint set is complicated such that the project…
Distributed stochastic proximal algorithm with random reshuffling for non-smooth finite-sum optimization
Xia Jiang, Xianlin Zeng, Jian Sun +2
The non-smooth finite-sum minimization is a fundamental problem in machine learning. This paper develops a distributed stochastic proximal-gradient algorithm with random reshufflin…