74 citations · 141 across the 4 of their papers we have counts for
5 papers
Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
Yang Liu, Yunan Luo, Yuanyi Zhong +3
Recent advances in deep reinforcement learning algorithms have shown great potential and success for solving many challenging real-world problems, including Go game and robotic app…
Stochastic Variance Reduction for Deep Q-learning
Wei-Ye Zhao, Xi-Ya Guan, Yang Liu +2
Recent advances in deep reinforcement learning have achieved human-level performance on a variety of real-world applications. However, the current algorithms still suffer from poor…
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.…
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…
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening
Frank S. He, Yang Liu, Alexander G. Schwing +1
We propose a novel training algorithm for reinforcement learning which combines the strength of deep Q-learning with a constrained optimization approach to tighten optimality and e…