3 citations · 3 across the 2 of their papers we have counts for
3 papers
An Exploration of Multicalibration Uniform Convergence Bounds
Harrison Rosenberg, Robi Bhattacharjee, Kassem Fawaz +1
Recent works have investigated the sample complexity necessary for fair machine learning. The most advanced of such sample complexity bounds are developed by analyzing multicalibra…
Analyzing Accuracy Loss in Randomized Smoothing Defenses
Yue Gao, Harrison Rosenberg, Kassem Fawaz +2
Recent advances in machine learning (ML) algorithms, especially deep neural networks (DNNs), have demonstrated remarkable success (sometimes exceeding human-level performance) on s…
A Geometric Perspective on the Transferability of Adversarial Directions
Zachary Charles, Harrison Rosenberg, Dimitris Papailiopoulos
State-of-the-art machine learning models frequently misclassify inputs that have been perturbed in an adversarial manner. Adversarial perturbations generated for a given input and…