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Spectral Subspace Clustering for Graphs with Feature Vectors.

, , , and . ICDM, page 231-240. IEEE Computer Society, (2013)

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Personalized Item Recommendation with Continuous Experience Evolution of Users using Brownian Motion., , and . CoRR, (2017)Personalized Embedding Propagation: Combining Neural Networks on Graphs with Personalized PageRank., , and . CoRR, (2018)ZooBP: Belief Propagation for Heterogeneous Networks., , , , and . PVLDB, 10 (5): 625-636 (2017)Assessing the Significance of Data Mining Results on Graphs with Feature Vectors., , , and . ICDM, page 270-279. IEEE Computer Society, (2012)Hyperbolae are No Hyperbole: Modelling Communities That are Not Cliques., , and . ICDM, page 330-339. IEEE Computer Society, (2016)Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data., , , and . ICDM, page 1220. IEEE Computer Society, (2010)Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms., , , and . ICDM, page 845-850. IEEE Computer Society, (2010)Intrinsic Degree: An Estimator of the Local Growth Rate in Graphs., , and . SISAP, volume 11223 of Lecture Notes in Computer Science, page 195-208. Springer, (2018)Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data., , , and . KDD, page 352-360. ACM, (2012)SMVC: semi-supervised multi-view clustering in subspace projections., , , and . KDD, page 253-262. ACM, (2014)