Wenda Zhou

Compressibility and Generalization in Large-Scale Deep Learning pdf

Ryan P. Adams, Victor Veitch, Peter Orbanz, 2018, ArXiv.

Denoising of structured random processes pdf

Shirin Jalali, Wenda Zhou, 2019, ArXiv.

Discrete Object Generation with Reversible Inductive Construction

Ryan P. Adams, Ari Seff, Farhan N. Damani, 2019, NeurIPS.

Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems pdf

Vahab S. Mirrokni, Arian Maleki, Haihao Lu, 2018, ArXiv.

Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions

Vahab S. Mirrokni, Arian Maleki, Haihao Lu, 2018, ICML.

Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data pdf

David M. Blei, Victor Veitch, Peter Orbanz, 2019, AISTATS.

Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach

Ryan P. Adams, Victor Veitch, Peter Orbanz, 2018, ICLR.