37 citations · 103 across the 10 of their papers we have counts for
5 papers · 1 filter
Trace-Norm Adversarial Examples
Ehsan Kazemi, Thomas Kerdreux, Liqiang Wang
White box adversarial perturbations are sought via iterative optimization algorithms most often minimizing an adversarial loss on a neighborhood of the original image, the so…
On Adversarial Bias and the Robustness of Fair Machine Learning
Hongyan Chang, Ta Duy Nguyen, Sasi Kumar Murakonda +2
Optimizing prediction accuracy can come at the expense of fairness. Towards minimizing discrimination against a group, fair machine learning algorithms strive to equalize the behav…
Submodular Maximization Through Barrier Functions
Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi +1
In this paper, we introduce a novel technique for constrained submodular maximization, inspired by barrier functions in continuous optimization. This connection not only improves t…
Regularized Submodular Maximization at Scale
Ehsan Kazemi, Shervin Minaee, Moran Feldman +1
In this paper, we propose scalable methods for maximizing a regularized submodular function expressed as the difference between a monotone submodular function an…
Streaming Submodular Maximization under a -Set System Constraint
Ran Haba, Ehsan Kazemi, Moran Feldman +1
In this paper, we propose a novel framework that converts streaming algorithms for monotone submodular maximization into streaming algorithms for non-monotone submodular maximizati…