80 citations · 101 across the 7 of their papers we have counts for
5 papers · 1 filter
ResMem: Learn what you can and memorize the rest
Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan +5
The impressive generalization performance of modern neural networks is attributed in part to their ability to implicitly memorize complex training patterns. Inspired by this, we ex…
Predicting Out-of-Distribution Error with the Projection Norm
Yaodong Yu, Zitong Yang, Alexander Wei +2
We propose a metric -- Projection Norm -- to predict a model's performance on out-of-distribution (OOD) data without access to ground truth labels. Projection Norm first uses model…
Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models
Zitong Yang, Yu Bai, Song Mei
Recent work showed that there could be a large gap between the classical uniform convergence bound and the actual test error of zero-training-error predictors (interpolators) such…
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition
Yaodong Yu, Zitong Yang, Edgar Dobriban +2
Adversarially trained models exhibit a large generalization gap: they can interpolate the training set even for large perturbation radii, but at the cost of large test error on cle…
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
Zitong Yang, Yaodong Yu, Chong You +2
The classical bias-variance trade-off predicts that bias decreases and variance increase with model complexity, leading to a U-shaped risk curve. Recent work calls this into questi…