2 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
Optimization and Optimizers for Adversarial Robustness
Hengyue Liang, Buyun Liang, Le Peng +3
Empirical robustness evaluation (RE) of deep learning models against adversarial perturbations entails solving nontrivial constrained optimization problems. Existing numerical algo…
cs.LG2023★ 2 cited
Welfare and Fairness Dynamics in Federated Learning: A Client Selection Perspective
Yash Travadi, Le Peng, Xuan Bi +2
Federated learning (FL) is a privacy-preserving learning technique that enables distributed computing devices to train shared learning models across data silos collaboratively. Exi…