6 citations · 12 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
Imbalanced Classification in Medical Imaging via Regrouping
Le Peng, Yash Travadi, Rui Zhang +2
We propose performing imbalanced classification by regrouping majority classes into small classes so that we turn the problem into balanced multiclass classification. This new idea…
A Prospective Observational Study to Investigate Performance of a Chest X-ray Artificial Intelligence Diagnostic Support Tool Across 12 U.S. Hospitals
Ju Sun, Le Peng, Taihui Li +14
Importance: An artificial intelligence (AI)-based model to predict COVID-19 likelihood from chest x-ray (CXR) findings can serve as an important adjunct to accelerate immediate cli…
Rethinking Transfer Learning for Medical Image Classification
Le Peng, Hengyue Liang, Gaoxiang Luo +2
Transfer learning (TL) from pretrained deep models is a standard practice in modern medical image classification (MIC). However, what levels of features to be reused are problem-de…