41 citations · 84 across the 20 of their papers we have counts for
11 papers · 1 filter
Revealing Strategic Interactions in Network Games Under Decaying Active Probing
Xiaoyu Xin, Longxu Zhang, Jinlong Lei +1
Revealing the interaction topology underlying strategic behavior is fundamental to prediction, intervention, and policy design in networked systems. Yet the interaction matrix is o…
A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements
Gehui Xu, Guanpu Chen, Baris Fidan +4
Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. W…
Global solution to sensor network localization: A non-convex potential game approach and its distributed implementation
Gehui Xu, Guanpu Chen, Yiguang Hong +3
Consider a sensor network consisting of both anchor and non-anchor nodes. We address the following sensor network localization (SNL) problem: given the physical locations of anchor…
Non-convex potential games for finding global solutions to sensor network localization
Gehui Xu, Guanpu Chen, Yiguang Hong +3
Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and th…
Riemannian Optimistic Algorithms
Xi Wang, Deming Yuan, Yiguang Hong +3
In this paper, we consider Riemannian online convex optimization with dynamic regret. First, we propose two novel algorithms, namely the Riemannian Online Optimistic Gradient Desce…
Distributed Online Convex Optimization with Adversarial Constraints: Reduced Cumulative Constraint Violation Bounds under Slater's Condition
Xinlei Yi, Xiuxian Li, Tao Yang +4
This paper considers distributed online convex optimization with adversarial constraints. In this setting, a network of agents makes decisions at each round, and then only a portio…
Distributed Non-Bayesian Learning for Games with Incomplete Information
Shijie Huang, Jinlong Lei, Yiguang Hong
We consider distributed learning problem in games with an unknown cost-relevant parameter, and aim to find the Nash equilibrium while learning the true parameter. Inspired by the s…
Defense for Advanced Persistent Threat with Inadvertent or Malicious Insider Threats
Ziqin Chen, Guanpu Chen, Yiguang Hong
In this paper, we propose a game-theoretical framework to investigate advanced persistent threat problems with two types of insider threats: malicious and inadvertent. Within this…
Distributed Algorithm for Continuous-type Bayesian Nash Equilibrium in Subnetwork Zero-sum Games
Hanzheng Zhang, Guanpu Chen, Yiguang Hong
In this paper, we consider a continuous-type Bayesian Nash equilibrium (BNE) seeking problem in subnetwork zero-sum games, which is a generalization of deterministic subnetwork zer…
No-Regret Learning in Network Stochastic Zero-Sum Games
Shijie Huang, Jinlong Lei, Yiguang Hong
No-regret learning has been widely used to compute a Nash equilibrium in two-person zero-sum games. However, there is still a lack of regret analysis for network stochastic zero-su…
On Faster Convergence of Scaled Sign Gradient Descent
Xiuxian Li, Kuo-Yi Lin, Li Li +2
Communication has been seen as a significant bottleneck in industrial applications over large-scale networks. To alleviate the communication burden, sign-based optimization algorit…