618 citations · 2.3k across the 40 of their papers we have counts for
10 papers · 1 filter
Reasoning in Vector Space: An Exploratory Study of Question Answering
Moontae Lee, Xiaodong He, Wen-tau Yih +3
Question answering tasks have shown remarkable progress with distributed vector representation. In this paper, we investigate the recently proposed Facebook bAbI tasks which consis…
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…
Stacked Attention Networks for Image Question Answering
Zichao Yang, Xiaodong He, Jianfeng Gao +2
This paper presents stacked attention networks (SANs) that learn to answer natural language questions from images. SANs use semantic representation of a question as query to search…
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…
Distributed Compressive Sensing: A Deep Learning Approach
Hamid Palangi, Rabab Ward, Li Deng
Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different c…
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…