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cs.LG2024
On the Benefits of Over-parameterization for Out-of-Distribution Generalization
Yifan Hao, Yong Lin, Difan Zou +1
In recent years, machine learning models have achieved success based on the independently and identically distributed assumption. However, this assumption can be easily violated in…
cs.LG2024
The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness
Yifan Hao, Tong Zhang
Recent empirical and theoretical studies have established the generalization capabilities of large machine learning models that are trained to (approximately or exactly) fit noisy…