64 citations · 177 across the 6 of their papers we have counts for
6 papers
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts
Kun Jin, Tongxin Yin, Zhongzhu Chen +4
We consider a federated learning (FL) system consisting of multiple clients and a server, where the clients aim to collaboratively learn a common decision model from their distribu…
Structural Stability of a Family of Group Formation Games
Chenlan Wang, Mehrdad Moharrami, Kun Jin +3
We introduce and study a group formation game in which individuals/agents, driven by self-interest, team up in disjoint groups so as to be in groups of high collective strength. Th…
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
Huan Zhang, Hongge Chen, Chaowei Xiao +4
A deep reinforcement learning (DRL) agent observes its states through observations, which may contain natural measurement errors or adversarial noises. Since the observations devia…
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
Yulong Cao, Chaowei Xiao, Dawei Yang +4
Deep neural networks (DNNs) are found to be vulnerable against adversarial examples, which are carefully crafted inputs with a small magnitude of perturbation aiming to induce arbi…
Characterizing Attacks on Deep Reinforcement Learning
Xinlei Pan, Chaowei Xiao, Warren He +8
Recent studies show that Deep Reinforcement Learning (DRL) models are vulnerable to adversarial attacks, which attack DRL models by adding small perturbations to the observations.…
Congestion games with resource reuse and applications in spectrum sharing
Sahand Haji Ali Ahmad, Mingyan Liu, Yunnan Wu
In this paper we consider an extension to the classical definition of congestion games (CG) in which multiple users share the same set of resources and their payoff for using any r…