306 citations · 2.2k across the 100 of their papers we have counts for
5 papers · 2 filters
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…
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.…
Stochastic Variance Reduction for Policy Gradient Estimation
Tianbing Xu, Qiang Liu, Jian Peng
Recent advances in policy gradient methods and deep learning have demonstrated their applicability for complex reinforcement learning problems. However, the variance of the perform…
Stein Variational Policy Gradient
Yang Liu, Prajit Ramachandran, Qiang Liu +1
Policy gradient methods have been successfully applied to many complex reinforcement learning problems. However, policy gradient methods suffer from high variance, slow convergence…