315 citations · 623 across the 37 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.CL2022★ 2 cited
NoisyTune: A Little Noise Can Help You Finetune Pretrained Language Models Better
Chuhan Wu, Fangzhao Wu, Tao Qi +2
Effectively finetuning pretrained language models (PLMs) is critical for their success in downstream tasks. However, PLMs may have risks in overfitting the pretraining tasks and da…
cs.IR2022★ 3 cited
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling
Chuhan Wu, Fangzhao Wu, Tao Qi +2
Federated learning (FL) is a feasible technique to learn personalized recommendation models from decentralized user data. Unfortunately, federated recommender systems are vulnerabl…
cs.LG2022★ 4 cited
Game of Privacy: Towards Better Federated Platform Collaboration under Privacy Restriction
Chuhan Wu, Fangzhao Wu, Tao Qi +4
Vertical federated learning (VFL) aims to train models from cross-silo data with different feature spaces stored on different platforms. Existing VFL methods usually assume all dat…