3 papers
cs.LG2025
Improved Regularization and Robustness for Fine-tuning in Neural Networks
Dongyue Li, Hongyang R. Zhang
A widely used algorithm for transfer learning is fine-tuning, where a pre-trained model is fine-tuned on a target task with a small amount of labeled data. When the capacity of the…
stat.ML2025
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers
Fan Yang, Hongyang R. Zhang, Sen Wu +2
The problem of learning one task using samples from another task is central to transfer learning. In this paper, we focus on answering the following question: when does combining t…
cs.LG2024
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations
Michael Zhang, Nimit S. Sohoni, Hongyang R. Zhang +2
Spurious correlations pose a major challenge for robust machine learning. Models trained with empirical risk minimization (ERM) may learn to rely on correlations between class labe…