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In AISTATS ."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Aditya Grover and Jure Leskovec. 2016. node2vec: Scalable feature learning for networks. In SIGKDD .  Aditya Grover and Jure Leskovec. 2016. node2vec: Scalable feature learning for networks. In SIGKDD .","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_1_7_1","unstructured":"Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In NeurIPS .  Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In NeurIPS ."},{"key":"e_1_3_2_1_8_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). Diederik P Kingma and Jimmy Ba. 2014. 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Finding community structure in networks using the eigenvectors of matrices. Physical review E (2006)."},{"key":"e_1_3_2_1_19_1","unstructured":"Jingchao Ni Shiyu Chang Xiao Liu Wei Cheng Haifeng Chen Dongkuan Xu and Xiang Zhang. 2018. Co-regularized deep multi-network embedding. In WWW .  Jingchao Ni Shiyu Chang Xiao Liu Wei Cheng Haifeng Chen Dongkuan Xu and Xiang Zhang. 2018. Co-regularized deep multi-network embedding. In WWW ."},{"key":"e_1_3_2_1_20_1","volume-title":"A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks. BMC bioinformatics","author":"Ou-Yang Le","year":"2017","unstructured":"Le Ou-Yang , Hong Yan , and Xiao-Fei Zhang . 2017. A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks. BMC bioinformatics ( 2017 ). Le Ou-Yang, Hong Yan, and Xiao-Fei Zhang. 2017. A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks. 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