6 citations · 12 across the 6 of their papers we have counts for
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cs.CL2023
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language Processing
Le Peng, Gaoxiang Luo, sicheng zhou +4
Language models (LMs) such as BERT and GPT have revolutionized natural language processing (NLP). However, the medical field faces challenges in training LMs due to limited data ac…
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…