88 citations · 139 across the 10 of their papers we have counts for
4 papers · 1 filter
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki
We study the problem of out-of-sample risk estimation in the high dimensional regime where both the sample size and number of features are large, and can be less than…
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Shuaiwen Wang, Wenda Zhou, Haihao Lu +2
Consider the following class of learning schemes: $$\hat{\boldsymbolβ} := \arg\min_{\boldsymbolβ}\;\sum_{j=1}^n \ell(\boldsymbol{x}_j^\top\boldsymbolβ; y_j) + λR(\boldsymbolβ),\qqu…
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
Victor Veitch, Morgane Austern, Wenda Zhou +2
Empirical risk minimization is the main tool for prediction problems, but its extension to relational data remains unsolved. We solve this problem using recent ideas from graph sam…
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach
Wenda Zhou, Victor Veitch, Morgane Austern +2
Modern neural networks are highly overparameterized, with capacity to substantially overfit to training data. Nevertheless, these networks often generalize well in practice. It has…