21 citations · 34 across the 3 of their papers we have counts for
3 papers
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification
Francisco Utrera, Evan Kravitz, N. Benjamin Erichson +2
Transfer learning has emerged as a powerful methodology for adapting pre-trained deep neural networks on image recognition tasks to new domains. This process consists of taking a n…
Boundary thickness and robustness in learning models
Yaoqing Yang, Rajiv Khanna, Yaodong Yu +5
Robustness of machine learning models to various adversarial and non-adversarial corruptions continues to be of interest. In this paper, we introduce the notion of the boundary thi…
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis +1
Bayesian coresets have emerged as a promising approach for implementing scalable Bayesian inference. The Bayesian coreset problem involves selecting a (weighted) subset of the data…