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Recent works reveal that network embedding techniques enable many machine learning models to handle diverse downstream tasks on graph structured data.
Visualizing data using t-sne
Laurens Van Der Maaten and Geoffrey Hinton · 2008
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Domain adaptation: Learning bounds and algorithms
Yishay Mansour, Mehryar Mohri, and Afshin Rostamizadeh · 2009
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Rolx: structural role extraction & mining in large graphs
Keith Henderson, Brian Gallagher, Tina Eliassi-Rad, Hanghang Tong, Sugato Basu, Leman Akoglu, Danai Koutra, Christos Faloutsos, and Lei Li · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Mining triadic closure patterns in social networks
Hong Huang, Jie Tang, Sen Wu, Lu Liu, and Xiaoming Fu · 2014
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Deepwalk: online learning of social representations
Bryan Perozzi, Rami Alrfou, and Steven Skiena · 2014
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor S. Lempitsky · 2015
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Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael I. Jordan · 2015
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Line: Large-scale information network embedding
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei · 2015
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Convolutional neural networks on graphs with fast localized spectral filtering
Michael Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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node2vec: Scalable feature learning for networks
Aditya Grover and Jure Leskovec · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2016
Cited alongside, same era.
Variational graph auto-encoders
Thomas N. Kipf and Max Welling · 2016
Cited alongside, same era.
Visualizing large-scale and high-dimensional data
Jian Tang, Jingzhou Liu, Ming Zhang, and Qiaozhu Mei · 2016
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Aminer: Mining deep knowledge from big scholar data
Jie Tang · 2016
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Revisiting semi-supervised learning with graph embeddings
Zhilin Yang, William W. Cohen, and Ruslan Salakhutdinov · 2016
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Domain adaptation for relation extraction with domain adversarial neural network
Multi-task domain adaptation for sequence tagging
Nanyun Peng and Mark Dredze · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
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Domain adaptation with adversarial training and graph embeddings
Firoj Alam, Shafiq R. Joty, and Muhammad Imran · 2018
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Graph matching and pseudo-label guided deep unsupervised domain adaptation
Debasmit Das and C. S. George Lee · 2018
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Learning structural node embeddings via diffusion wavelets
Claire Donnat, Marinka Zitnik, David Hallac, and Jure Leskovec · 2018
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Dynamic network embedding : An extended approach for skip-gram based network embedding
Lun Du, Yun Wang, Guojie Song, Zhicong Lu, and Junshan Wang · 2018
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Lisheng Fu, Thien Huu Nguyen, Bonan Min, and Ralph Grishman · 2017
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Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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On generalizing neural node embedding methods to multi-network problems
Mark Heimann and Danai Koutra · 2017
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Graph-based isometry invariant representation learning
Renata Khasanova and Pascal Frossard · 2017
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Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang, and Stephen Paul Smolley · 2017
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Mego2vec: Embedding matched ego networks for user alignment across social networks
Jing Zhang, Bo Chen, Xianming Wang, Hong Chen, Cuiping Li, Fengmei Jin, Guojie Song, and Yutao Zhang · 2018
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Chinese medical concept normalization by using text and comorbidity network embedding
Yizhou Zhang, Xiaojun Ma, and Guojie Song · 2018
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Sepne: Bringing separability to network embedding
Ziyao Li, Liang Zhang, and Guojie Song · 2019
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Tag2vec: Learning tag representations in tag networks
Junshan Wang, Zhicong Lu, Guojie Song, Yue Fan, Lun Du, and Wei Lin · 2019
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