2 citations · 7 across the 15 of their papers we have counts for
5 papers · 1 filter
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework
Fangyikang Wang, Huminhao Zhu, Chao Zhang +2
Particle-based Variational Inference (ParVI) methods approximate the target distribution by iteratively evolving finite weighted particle systems. Recent advances of ParVI methods…
Towards Optimal Randomized Strategies in Adversarial Example Game
Jiahao Xie, Chao Zhang, Weijie Liu +2
The vulnerability of deep neural network models to adversarial example attacks is a practical challenge in many artificial intelligence applications. A recent line of work shows th…
PACER: A Fully Push-forward-based Distributional Reinforcement Learning Algorithm
Wensong Bai, Chao Zhang, Yichao Fu +3
In this paper, we propose the first fully push-forward-based distributional reinforcement learning algorithm, named PACER, which consists of a distributional critic, a stochastic a…
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization
Zebang Shen, Hui Qian, Tongzhou Mu +1
Nowadays, algorithms with fast convergence, small memory footprints, and low per-iteration complexity are particularly favorable for artificial intelligence applications. In this p…
An Asynchronous Decentralized Algorithm for Wasserstein Barycenter Problem
Chao Zhang, Hui Qian, Jiahao Xie
Wasserstein Barycenter Problem (WBP) has recently received much attention in the field of artificial intelligence. In this paper, we focus on the decentralized setting for WBP and…