1.3k citations · 1.7k across the 19 of their papers we have counts for
4 papers · 1 filter
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu, Yao Li, Chongruo Wu +1
We present a new algorithm to train a robust neural network against adversarial attacks. Our algorithm is motivated by the following two ideas. First, although recent work has demo…
Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient
Liu Liu, Xuanqing Liu, Cho-Jui Hsieh +1
Trust region and cubic regularization methods have demonstrated good performance in small scale non-convex optimization, showing the ability to escape from saddle points. Each iter…
Fast Variance Reduction Method with Stochastic Batch Size
Xuanqing Liu, Cho-Jui Hsieh
In this paper we study a family of variance reduction methods with randomized batch size---at each step, the algorithm first randomly chooses the batch size and then selects a batc…
Rob-GAN: Generator, Discriminator, and Adversarial Attacker
Xuanqing Liu, Cho-Jui Hsieh
We study two important concepts in adversarial deep learning---adversarial training and generative adversarial network (GAN). Adversarial training is the technique used to improve…