Graph Recurrent Networks With Attributed Random Walks-Reference-Cited by-同舟云学术

Graph Recurrent Networks With Attributed Random Walks

Published:2019-07-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
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Author:

Huang Xiao¹,Song Qingquan¹,Li Yuening¹,Hu Xia¹

Affiliation:

1. Texas A&M University, College Station, TX, USA

Funder

National Science Foundation

Defense Advanced Research Projects Agency

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3292500.3330941

Reference45 articles.

1. Lars Backstrom and Jure Leskovec. 2011. Supervised Random Walks: Predicting and Recommending Links in Social Networks. In WSDM . 635--644. 10.1145/1935826.1935914 Lars Backstrom and Jure Leskovec. 2011. Supervised Random Walks: Predicting and Recommending Links in Social Networks. In WSDM . 635--644. 10.1145/1935826.1935914

2. Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. In ICLR . Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. In ICLR .

3. Heterogeneous Network Embedding via Deep Architectures

4. Jie Chen Tengfei Ma and Cao Xiao. 2018. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In ICLR . Jie Chen Tengfei Ma and Cao Xiao. 2018. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In ICLR .

5. Random walks in recommender systems

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