11 citations · 14 across the 4 of their papers we have counts for
5 papers · 1 filter
Discrete Action On-Policy Learning with Action-Value Critic
Yuguang Yue, Yunhao Tang, Mingzhang Yin +1
Reinforcement learning (RL) in discrete action space is ubiquitous in real-world applications, but its complexity grows exponentially with the action-space dimension, making it cha…
Semi-Implicit Generative Model
Mingzhang Yin, Mingyuan Zhou
To combine explicit and implicit generative models, we introduce semi-implicit generator (SIG) as a flexible hierarchical model that can be trained in the maximum likelihood framew…
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables
Mingzhang Yin, Yuguang Yue, Mingyuan Zhou
To address the challenge of backpropagating the gradient through categorical variables, we propose the augment-REINFORCE-swap-merge (ARSM) gradient estimator that is unbiased and h…
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks
Mingzhang Yin, Mingyuan Zhou
To backpropagate the gradients through stochastic binary layers, we propose the augment-REINFORCE-merge (ARM) estimator that is unbiased, exhibits low variance, and has low computa…
Semi-Implicit Variational Inference
Mingzhang Yin, Mingyuan Zhou
Semi-implicit variational inference (SIVI) is introduced to expand the commonly used analytic variational distribution family, by mixing the variational parameter with a flexible d…