99 citations · 316 across the 43 of their papers we have counts for
3 papers · 1 filter
Learning Privately over Distributed Features: An ADMM Sharing Approach
Yaochen Hu, Peng Liu, Linglong Kong +1
Distributed machine learning has been widely studied in order to handle exploding amount of data. In this paper, we study an important yet less visited distributed learning problem…
Distributional Reinforcement Learning for Efficient Exploration
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao +3
In distributional reinforcement learning (RL), the estimated distribution of value function models both the parametric and intrinsic uncertainties. We propose a novel and efficient…
Deep Reinforcement Learning with Decorrelation
Borislav Mavrin, Hengshuai Yao, Linglong Kong
Learning an effective representation for high-dimensional data is a challenging problem in reinforcement learning (RL). Deep reinforcement learning (DRL) such as Deep Q networks (D…