709 citations · 2.5k across the 39 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning with a Natural Language Action Space
Ji He, Jianshu Chen, Xiaodong He +4
This paper introduces a novel architecture for reinforcement learning with deep neural networks designed to handle state and action spaces characterized by natural language, as fou…
Recurrent Reinforcement Learning: A Hybrid Approach
Xiujun Li, Lihong Li, Jianfeng Gao +4
Successful applications of reinforcement learning in real-world problems often require dealing with partially observable states. It is in general very challenging to construct and…
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
Jianshu Chen, Ji He, Yelong Shen +5
We develop a fully discriminative learning approach for supervised Latent Dirichlet Allocation (LDA) model using Back Propagation (i.e., BP-sLDA), which maximizes the posterior pro…
Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval
Hamid Palangi, Li Deng, Yelong Shen +5
This paper develops a model that addresses sentence embedding, a hot topic in current natural language processing research, using recurrent neural networks with Long Short-Term Mem…