66 citations · 116 across the 18 of their papers we have counts for
4 papers · 1 filter
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling
Junyuan Hong, Lingjuan Lyu, Jiayu Zhou +1
As deep learning blooms with growing demand for computation and data resources, outsourcing model training to a powerful cloud server becomes an attractive alternative to training…
Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork
Haotao Wang, Junyuan Hong, Aston Zhang +2
Deep neural networks (DNNs) are vulnerable to backdoor attacks. Previous works have shown it extremely challenging to unlearn the undesired backdoor behavior from the network, sinc…
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Haotao Wang, Junyuan Hong, Jiayu Zhou +1
Increasing concerns have been raised on deep learning fairness in recent years. Existing fairness-aware machine learning methods mainly focus on the fairness of in-distribution dat…
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization
Junyuan Hong, Haotao Wang, Zhangyang Wang +1
Federated learning (FL) provides a distributed learning framework for multiple participants to collaborate learning without sharing raw data. In many practical FL scenarios, partic…