3 citations · 7 across the 7 of their papers we have counts for
7 papers
Adaptive Requesting in Decentralized Edge Networks via Non-Stationary Bandits
Yi Zhuang, Kun Yang, Xingran Chen
We study a decentralized collaborative requesting problem that aims to optimize the information freshness of time-sensitive clients in edge networks consisting of multiple clients,…
Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation
Kun Yang, Neena Imam
Federated Learning (FL) enables collaborative machine learning across decentralized data sources without sharing raw data. It offers a promising approach to privacy-preserving AI.…
Financial Data Analysis with Robust Federated Logistic Regression
Kun Yang, Nikhil Krishnan, Sanjeev R. Kulkarni
In this study, we focus on the analysis of financial data in a federated setting, wherein data is distributed across multiple clients or locations, and the raw data never leaves th…
A Seesaw Model Attack Algorithm for Distributed Learning
Kun Yang, Tianyi Luo, Yanjie Dong +1
We investigate the Byzantine attack problem within the context of model training in distributed learning systems. While ensuring the convergence of current model training processes…
Training Latency Minimization for Model-Splitting Allowed Federated Edge Learning
Yao Wen, Guopeng Zhang, Kezhi Wang +1
To alleviate the shortage of computing power faced by clients in training deep neural networks (DNNs) using federated learning (FL), we leverage the edge computing and split learni…
Byzantine-Robust Clustered Federated Learning
Zhixu Tao, Kun Yang, Sanjeev R. Kulkarni
This paper focuses on the problem of adversarial attacks from Byzantine machines in a Federated Learning setting where non-Byzantine machines can be partitioned into disjoint clust…
Task-load-Aware Game-Theoretic Framework for Wireless Federated Learning
Jiawei Liu, Guopeng Zhang, Kezhi Wang +1
Federated learning (FL) has been proposed as a popular learning framework to protect the users' data privacy but it has difficulties in motivating the users to participate in task…