8 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 2 cited
Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy E. J. Cohen, Zinan Lin +5
Generative adversarial networks (GANs) are often billed as "universal distribution learners", but precisely what distributions they can represent and learn is still an open questio…
cs.LG2018★ 8 cited
Limitations of the Lipschitz constant as a defense against adversarial examples
Todd Huster, Cho-Yu Jason Chiang, Ritu Chadha
Several recent papers have discussed utilizing Lipschitz constants to limit the susceptibility of neural networks to adversarial examples. We analyze recently proposed methods for…
cs.DC2010
On Optimal Deadlock Detection Scheduling
Yibei Ling, Shigang Chen, Cho-Yu Jason Chiang
Deadlock detection scheduling is an important, yet often overlooked problem that can significantly affect the overall performance of deadlock handling. Excessive initiation of dead…