16 citations · 46 across the 5 of their papers we have counts for
5 papers
Privacy-Preserving Push-Pull Method for Decentralized Optimization via State Decomposition
Huqiang Cheng, Xiaofeng Liao, Huaqing Li +1
Distributed optimization is manifesting great potential in multiple fields, e.g., machine learning, control, and resource allocation. Existing decentralized optimization algorithms…
(Corrected Version) Push-LSVRG-UP: Distributed Stochastic Optimization over Unbalanced Directed Networks with Uncoordinated Triggered Probabilities
Jinhui Hu, Guo Chen, Huaqing Li +2
Distributed stochastic optimization, arising in the crossing and integration of traditional stochastic optimization, distributed computing and storage, and network science, has adv…
Distributed Online Private Learning of Convex Nondecomposable Objectives
Huqiang Cheng, Xiaofeng Liao, Huaqing Li
We deal with a general distributed constrained online learning problem with privacy over time-varying networks, where a class of nondecomposable objectives are considered. Under th…
S-DIGing: A Stochastic Gradient Tracking Algorithm for Distributed Optimization
Huaqing Li, Lifeng Zheng, Zheng Wang +3
In this paper, we study convex optimization problems where agents of a network cooperatively minimize the global objective function which consists of multiple local objective funct…
Geometrical Convergence Rate for Distributed Optimization with Time-Varying Directed Graphs and Uncoordinated Step-Sizes
Qingguo Lü, Huaqing Li
This paper studies a class of distributed optimization algorithms by a set of agents, where each agent has only access to its own local convex objective function, and jointly minim…