192 citations · 249 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 2 cited
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems
Pouria Mahdavinia, Yuyang Deng, Haochuan Li +1
Despite the established convergence theory of Optimistic Gradient Descent Ascent (OGDA) and Extragradient (EG) methods for the convex-concave minimax problems, little is known abou…
cs.LG2019★ 55 cited
Convergence of Adversarial Training in Overparametrized Neural Networks
Ruiqi Gao, Tianle Cai, Haochuan Li +3
Neural networks are vulnerable to adversarial examples, i.e. inputs that are imperceptibly perturbed from natural data and yet incorrectly classified by the network. Adversarial tr…
cs.LG2018★ 192 cited
Gradient Descent Finds Global Minima of Deep Neural Networks
Simon S. Du, Jason D. Lee, Haochuan Li +2
Gradient descent finds a global minimum in training deep neural networks despite the objective function being non-convex. The current paper proves gradient descent achieves zero tr…