24 citations · 75 across the 22 of their papers we have counts for
8 papers · 1 filter
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning
Yue Cui, Liuyi Yao, Zitao Li +3
Vertical Federated Learning (VFL) has emerged as a popular machine learning paradigm, enabling model training across the data and the task parties with different features about the…
An Auction-based Marketplace for Model Trading in Federated Learning
Yue Cui, Liuyi Yao, Yaliang Li +3
Federated learning (FL) is increasingly recognized for its efficacy in training models using locally distributed data. However, the proper valuation of shared data in this collabor…
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models
Zhenqing Ling, Daoyuan Chen, Liuyi Yao +2
The confluence of Federated Learning (FL) and Large Language Models (LLMs) is ushering in a new era in privacy-preserving natural language processing. However, the intensive memory…
Efficient Personalized Federated Learning via Sparse Model-Adaptation
Daoyuan Chen, Liuyi Yao, Dawei Gao +2
Federated Learning (FL) aims to train machine learning models for multiple clients without sharing their own private data. Due to the heterogeneity of clients' local data distribut…
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks
Zeyu Qin, Liuyi Yao, Daoyuan Chen +3
In this work, besides improving prediction accuracy, we study whether personalization could bring robustness benefits to backdoor attacks. We conduct the first study of backdoor at…
A Benchmark for Federated Hetero-Task Learning
Liuyi Yao, Dawei Gao, Zhen Wang +7
To investigate the heterogeneity in federated learning in real-world scenarios, we generalize the classic federated learning to federated hetero-task learning, which emphasizes the…
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
Zhen Wang, Weirui Kuang, Yuexiang Xie +4
The incredible development of federated learning (FL) has benefited various tasks in the domains of computer vision and natural language processing, and the existing frameworks suc…
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
Yuexiang Xie, Zhen Wang, Dawei Gao +6
Although remarkable progress has been made by existing federated learning (FL) platforms to provide infrastructures for development, these platforms may not well tackle the challen…