18 citations · 26 across the 3 of their papers we have counts for
3 papers
cs.LG2022
On the Perils of Cascading Robust Classifiers
Ravi Mangal, Zifan Wang, Chi Zhang +3
Ensembling certifiably robust neural networks is a promising approach for improving the \emph{certified robust accuracy} of neural models. Black-box ensembles that assume only quer…
physics.flu-dyn2020★ 8 cited
Generative Adversarial Networks with Physical Evaluators for Spray Simulation of Pintle Injector
Hao Ma, Botao Zhang, Chi Zhang +1
Due to the adjustable geometry, pintle injectors are specially suitable for the liquid rocket engines which require a widely throttleable range. While applying the conventional com…
cs.LG2018★ 18 cited
Learning with Non-Convex Truncated Losses by SGD
Yi Xu, Shenghuo Zhu, Sen Yang +3
Learning with a {\it convex loss} function has been a dominating paradigm for many years. It remains an interesting question how non-convex loss functions help improve the generali…