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20172023
most citedRippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

1.2k citations · 3.1k across the 15 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

cs.CV2018★ 2 cited

Visual-Texual Emotion Analysis with Deep Coupled Video and Danmu Neural Networks

Chenchen Li, Jialin Wang, Hongwei Wang +3

User emotion analysis toward videos is to automatically recognize the general emotional status of viewers from the multimedia content embedded in the online video stream. Existing…

cs.CL2018★ 1 cited

Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks

Chang Xu, Weiran Huang, Hongwei Wang +2

Recurrent Neural Networks (RNNs) have been widely used in processing natural language tasks and achieve huge success. Traditional RNNs usually treat each token in a sentence unifor…

cs.LG2018★ 28 cited

AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods

Zhiming Zhou, Qingru Zhang, Guansong Lu +3

Adam is shown not being able to converge to the optimal solution in certain cases. Researchers recently propose several algorithms to avoid the issue of non-convergence of Adam, bu…

cs.LG2018★ 8 cited

Understanding the Effectiveness of Lipschitz-Continuity in Generative Adversarial Nets

Zhiming Zhou, Yuxuan Song, Lantao Yu +5

In this paper, we investigate the underlying factor that leads to failure and success in the training of GANs. We study the property of the optimal discriminative function and show…

cs.IR2018★ 1.2k cited

RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

Hongwei Wang, Fuzheng Zhang, Jialin Wang +4

To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve…

stat.ML2018★ 190 cited

DKN: Deep Knowledge-Aware Network for News Recommendation

Hongwei Wang, Fuzheng Zhang, Xing Xie +1

Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users. In general, news language is highly condensed, full…