6 citations · 7 across the 11 of their papers we have counts for
4 papers · 1 filter
DeRelayL: Sustainable Decentralized Relay Learning
Haihan Duan, Tengfei Ma, Yuyang Qin +4
In the era of big data, large-scale machine learning models have revolutionized various fields, driving significant advancements. However, large-scale model training demands high f…
A Nesterov-Accelerated Byzantine-Robust Federated Learning
Lihan Xu, Xiaoyi Fan, Gang Wang +3
We investigate robust federated learning, where a group of workers collaboratively train a shared model under the orchestration of a central server in the presence of Byzantine adv…
CO-PFL: Contribution-Oriented Personalized Federated Learning for Heterogeneous Networks
Ke Xing, Yanjie Dong, Xiaoyi Fan +4
Personalized federated learning (PFL) addresses a critical challenge of collaboratively training customized models for clients with heterogeneous and scarce local data. Conventiona…
Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers
Qi Deng, Shuaicheng Niu, Ronghao Zhang +4
Test-time adaptation (TTA) aims to fine-tune a trained model online using unlabeled testing data to adapt to new environments or out-of-distribution data, demonstrating broad appli…