92 citations · 113 across the 6 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2023★ 2 cited
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning
Kaijie Zhu, Jindong Wang, Xixu Hu +2
Deep neural networks are susceptible to adversarial examples, posing a significant security risk in critical applications. Adversarial Training (AT) is a well-established technique…
cs.LG2023
Frustratingly Easy Model Generalization by Dummy Risk Minimization
Juncheng Wang, Jindong Wang, Xixu Hu +2
Empirical risk minimization (ERM) is a fundamental machine learning paradigm. However, its generalization ability is limited in various tasks. In this paper, we devise Dummy Risk M…
cs.LG2023★ 19 cited
FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning
Wang Lu, Xixu Hu, Jindong Wang +1
Federated learning (FL) has emerged as a new paradigm for privacy-preserving computation in recent years. Unfortunately, FL faces two critical challenges that hinder its actual per…