25 citations · 56 across the 17 of their papers we have counts for
6 papers · 1 filter
Policy Disruption in Reinforcement Learning:Adversarial Attack with Large Language Models and Critical State Identification
Junyong Jiang, Buwei Tian, Chenxing Xu +2
Reinforcement learning (RL) has achieved remarkable success in fields like robotics and autonomous driving, but adversarial attacks designed to mislead RL systems remain challengin…
Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning
Shuo Tang, Rui Ye, Chenxin Xu +3
Decentralized and lifelong-adaptive multi-agent collaborative learning aims to enhance collaboration among multiple agents without a central server, with each agent solving varied…
Compatible Transformer for Irregularly Sampled Multivariate Time Series
Yuxi Wei, Juntong Peng, Tong He +4
To analyze multivariate time series, most previous methods assume regular subsampling of time series, where the interval between adjacent measurements and the number of samples rem…
FedDisco: Federated Learning with Discrepancy-Aware Collaboration
Rui Ye, Mingkai Xu, Jianyu Wang +3
This work considers the category distribution heterogeneity in federated learning. This issue is due to biased labeling preferences at multiple clients and is a typical setting of…
FedFM: Anchor-based Feature Matching for Data Heterogeneity in Federated Learning
Rui Ye, Zhenyang Ni, Chenxin Xu +3
One of the key challenges in federated learning (FL) is local data distribution heterogeneity across clients, which may cause inconsistent feature spaces across clients. To address…
Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks
Chenxin Xu, Rong Xia, Yong Xiao +3
With the fast growing demand on new services and applications as well as the increasing awareness of data protection, traditional centralized traffic classification approaches are…