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HiCS: High Contrast Subspaces for Density-Based Outlier Ranking.

, , and . ICDE, page 1037-1048. IEEE Computer Society, (2012)

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Including Multi-feature Interactions and Redundancy for Feature Ranking in Mixed Datasets., , , , and . ECML/PKDD (1), volume 10534 of Lecture Notes in Computer Science, page 239-255. Springer, (2017)OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces., , , and . ECML/PKDD (2), volume 7524 of Lecture Notes in Computer Science, page 828-832. Springer, (2012)Spectral Graph Complexity., , , , and . WWW (Companion Volume), page 308-309. ACM, (2019)Flexible Subspace Search for Outlier Detection and Description.. LWA, page 121. Universitätsbibliothek Bamberg, (2013)Outlier Ranking via Subspace Analysis in Multiple Views of the Data., , , , and . ICDM, page 529-538. IEEE Computer Society, (2012)Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data., , , , and . ICDM, page 377-386. IEEE Computer Society, (2009)Flexible Fault Tolerant Subspace Clustering for Data with Missing Values., , , and . ICDM, page 231-240. IEEE Computer Society, (2011)Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data., , , and . ICDM, page 937-942. IEEE Computer Society, (2013)NetLSD: Hearing the Shape of a Graph., , , , and . KDD, page 2347-2356. ACM, (2018)Unsupervised interaction-preserving discretization of multivariate data., , , and . Data Min. Knowl. Discov., 28 (5-6): 1366-1397 (2014)