306 citations · 2.2k across the 100 of their papers we have counts for
13 papers · 1 filter
Stein Variational Message Passing for Continuous Graphical Models
Dilin Wang, Zhe Zeng, Qiang Liu
We propose a novel distributed inference algorithm for continuous graphical models, by extending Stein variational gradient descent (SVGD) to leverage the Markov dependency structu…
On the Discrimination-Generalization Tradeoff in GANs
Pengchuan Zhang, Qiang Liu, Dengyong Zhou +2
Generative adversarial training can be generally understood as minimizing certain moment matching loss defined by a set of discriminator functions, typically neural networks. The d…
Efficient Localized Inference for Large Graphical Models
Jinglin Chen, Jian Peng, Qiang Liu
We propose a new localized inference algorithm for answering marginalization queries in large graphical models with the correlation decay property. Given a query variable and a lar…
Learning Infinite RBMs with Frank-Wolfe
Wei Ping, Qiang Liu, Alexander Ihler
In this work, we propose an infinite restricted Boltzmann machine~(RBM), whose maximum likelihood estimation~(MLE) corresponds to a constrained convex optimization. We consider the…
Energy-efficient Amortized Inference with Cascaded Deep Classifiers
Jiaqi Guan, Yang Liu, Qiang Liu +1
Deep neural networks have been remarkable successful in various AI tasks but often cast high computation and energy cost for energy-constrained applications such as mobile sensing.…
Action-depedent Control Variates for Policy Optimization via Stein's Identity
Hao Liu, Yihao Feng, Yi Mao +3
Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems. However, it still often suffers from the large variance issue on…