18 citations · 57 across the 16 of their papers we have counts for
16 papers
A Unified Zeroth-Order Approach for Decentralized Minimax Optimization
Haoyuan Cai, Yike Zhao, Aleksandar Armacki +2
We propose ZOMA, a unified Zeroth-Order decentralized accelerated MinimAx framework for multi-agent nonconvex Polyak--Łojasiewicz minimax optimization. The proposed framework only…
Online Game with Time-Varying Coupled Inequality Constraints
Min Meng, Xiuxian Li, Yiguang Hong +2
In this paper, online game is studied, where at each time, a group of players aim at selfishly minimizing their own time-varying cost function simultaneously subject to time-varyin…
A Distributed Iterative Tikhonov Method for Networked Monotone Aggregative Hierarchical Stochastic Games
Jinlong Lei, Uday V. Shanbhag, Jie Chen
We consider a class of nonsmooth aggregative games over networks in stochastic regimes, where each player is characterized by a composite cost function , is a smooth…
A Survey of Decision Making in Adversarial Games
Xiuxian Li, Min Meng, Yiguang Hong +1
Game theory has by now found numerous applications in various fields, including economics, industry, jurisprudence, and artificial intelligence, where each player only cares about…
An Optimal Distributed Algorithm with Operator Extrapolation for Stochastic Aggregative Games
Tongyu Wang, Peng Yi, Jie Chen
This work studies Nash equilibrium seeking for a class of stochastic aggregative games, where each player has an expectation-valued objective function depending on its local strate…
Distributed coordination for seeking the optimal Nash equilibrium of aggregative games
Xiaoyu Ma, Jinlong Lei, Peng Yi +1
This paper aims to design a distributed coordination algorithm for solving a multi-agent decision problem with a hierarchical structure. The primary goal is to search the Nash equi…
No-regret distributed learning in subnetwork zero-sum games
Shijie Huang, Jinlong Lei, Yiguang Hong +2
In this paper, we consider a distributed learning problem in a subnetwork zero-sum game, where agents are competing in different subnetworks. These agents are connected through tim…
Distributed Variable Sample-size Stochastic Optimization with Fixed Step-sizes
Jinlong Lei, Peng Yi, Jie Chen +1
The paper considers distributed stochastic optimization over randomly switching networks, where agents collaboratively minimize the average of all agents' local expectation-valued…
Composition and Application of Current Advanced Driving Assistance System: A Review
Xinran Li, Kuo-Yi Lin, Min Meng +4
Due to the growing awareness of driving safety and the development of sophisticated technologies, advanced driving assistance system (ADAS) has been equipped in more and more vehic…
Decentralized Online Learning for Noncooperative Games in Dynamic Environments
Min Meng, Xiuxian Li, Yiguang Hong +2
Decentralized online learning for seeking generalized Nash equilibrium (GNE) of noncooperative games in dynamic environments is studied in this paper. Each player aims at selfishly…
Distributed Optimization with Projection-free Dynamics
Guanpu Chen, Peng Yi, Yiguang Hong +1
We consider continuous-time dynamics for distributed optimization with set constraints in the paper. To handle the computational complexity of projection-based dynamics due to solv…
Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Pose
Hongsuk Choi, Gyeongsik Moon, Kyoung Mu Lee
Most of the recent deep learning-based 3D human pose and mesh estimation methods regress the pose and shape parameters of human mesh models, such as SMPL and MANO, from an input im…
Linearly Convergent Algorithm with Variance Reduction for Distributed Stochastic Optimization
Jinlong Lei, Peng Yi, Jie Chen +1
This paper considers a distributed stochastic strongly convex optimization, where agents connected over a network aim to cooperatively minimize the average of all agents' local cos…
Dynamical Primal-Dual Accelerated Method with Applications to Network Optimization
Xianlin Zeng, Jinlong Lei, Jie Chen
This paper develops a continuous-time primal-dual accelerated method with an increasing damping coefficient for a class of convex optimization problems with affine equality constra…
Distributed Computation of Linear Matrix Equations: An Optimization Perspective
Xianlin Zeng, Shu Liang, Yiguang Hong +1
This paper investigates the distributed computation of the well-known linear matrix equation in the form of , with the matrices A, B, X, and F of appropriate dimensions, o…
Scalable Computation of Regularized Precision Matrices via Stochastic Optimization
Yves F. Atchadé, Rahul Mazumder, Jie Chen
We consider the problem of computing a positive definite inverse covariance matrix aka precision matrix which optimizes a regularized Gaussian maximum lik…