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This paper describes a general framework for learning Higher-Order Network Embeddings (HONE) from graph data based on network motifs.
Some mathematical notes on three-mode factor analysis
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Using ghost edges for classification in sparsely labeled networks. In SIGKDD
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Ranking Links on the Web: Search and Surf Engines
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Deep learning via semi-supervised embedding. In ICML . 1168–1175
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Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems. In IEEE International Conference of Data Mining
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Convolutional neural networks on graphs with fast localized spectral filtering. In Advances in Neural Information Processing Systems . 3844–3852
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016 · 2016
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node2vec: Scalable feature learning for networks. In SIGKDD . 855–864
Aditya Grover and Jure Leskovec. 2016 · 2016
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Learning Convolutional Neural Networks for Graphs. In arXiv:1605.05273
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Parallel Collective Factorization for Modeling Large Heterogeneous Networks. In Social Network Analysis and Mining . 30
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Structural deep network embedding. In SIGKDD . 1225–1234
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HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks
Chuan Shi, Xiangnan Kong, Yue Huang, S Yu Philip, and Bin Wu. 2014 · 2014
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NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion
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Efficient Graphlet Counting for Large Networks. In ICDM . 10
Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, and Nick Duffield. 2015 · 2015
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GraRep: Learning graph representations with global structural information. In CIKM . ACM, 891–900
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Convolutional networks on graphs for learning molecular fingerprints. In NIPS
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Revisiting semi-supervised learning with graph embeddings
Zhilin Yang, William W Cohen, and Ruslan Salakhutdinov. 2016 · 2016
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Deep Gaussian Embedding of Attributed Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski and Stephan Günnemann. 2017 · 2017
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Learning community embedding with community detection and node embedding on graphs. In CIKM . 377–386
Sandro Cavallari, Vincent W Zheng, Hongyun Cai, Kevin Chen-Chuan Chang, and Erik Cambria. 2017 · 2017
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Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction
Connor W Coley, Regina Barzilay, William H Green, Tommi S Jaakkola, and Klavs F Jensen. 2017 · 2017
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metapath2vec: Scalable Representation Learning for Heterogeneous Networks. In SIGKDD
Yuxiao Dong, Nitesh V Chawla, and Ananthram Swami. 2017 · 2017
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Semi-supervised classification with graph convolutional networks. In ICLR
Thomas N Kipf and Max Welling. 2017 · 2017
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Skip-Graph: Learning graph embeddings with an encoder-decoder model. In ICLR OpenReview
John Boaz Lee and X. Kong. 2017 · 2017
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SEANO: Semi-supervised Embedding in Attributed Networks with Outliers. In arXiv:1703.08100
Jiongqian Liang, Peter Jacobs, and Srinivasan Parthasarathy. 2017 · 2017
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Struc2Vec: Learning Node Representations from Structural Identity. In SIGKDD
Leonardo F.R. Ribeiro, Pedro H.P. Saverese, and Daniel R. Figueiredo. 2017 · 2017
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Learning Role-based Graph Embeddings. In arXiv:1802.02896
Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, and Hoda Eldardiry. 2018 · 2018
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Network Classification and Categorization. In International Conference on Complex Networks (CompleNet)
James P. Canning, Emma E. Ingram, Sammantha Nowak-Wolff, Adriana M. Ortiz, Nesreen K. Ahmed, Ryan A. Rossi, Karl R. B. Schmitt, and Sucheta Soundarajan. 2018 · 2018
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Graph Classification using Structural Attention. In SIGKDD
John Boaz Lee, Ryan Rossi, and Xiangnan Kong. 2018 · 2018
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Continuous-Time Dynamic Network Embeddings. In WWW BigNet
Giang Hoang Nguyen, John Boaz Lee, Ryan A. Rossi, Nesreen K. Ahmed, Eunyee Koh, and Sungchul Kim. 2018 · 2018
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DyLink2Vec: Effective Feature Representation for Link Prediction in Dynamic Networks
Mahmudur Rahman, Tanay Kumar Saha, Mohammad Al Hasan, Kevin S Xu, and Chandan K Reddy. 2018 · 2018
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Tanay Kumar Saha, Thomas Williams, Mohammad Al Hasan, Shafiq Joty, and Nicholas K Varberg. 2018 · 2018
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