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Optimal construction of k-nearest-neighbor graphs for identifying noisy clusters.

, , and . Theor. Comput. Sci., 410 (19): 1749-1764 (2009)

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Hitting and commute times in large random neighborhood graphs., , and . J. Mach. Learn. Res., 15 (1): 1751-1798 (2014)A Compression Approach to Support Vector Model Selection., , and . J. Mach. Learn. Res., (2004)Optimal construction of k-nearest-neighbor graphs for identifying noisy clusters., , and . Theor. Comput. Sci., 410 (19): 1749-1764 (2009)Measures of distortion for machine learning., and . NeurIPS, page 4891-4900. (2018)From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians., , and . COLT, volume 3559 of Lecture Notes in Computer Science, page 470-485. Springer, (2005)Consistent Procedures for Cluster Tree Estimation and Pruning., , , and . IEEE Trans. Information Theory, 60 (12): 7900-7912 (2014)Risk-Based Generalizations of f-divergences., , and . ICML, page 417-424. Omnipress, (2011)Getting lost in space: Large sample analysis of the resistance distance., , and . NIPS, page 2622-2630. Curran Associates, Inc., (2010)Statistical learning with similarity and dissimilarity functions.. Berlin Institute of Technology, (2004)Graph Laplacians and their Convergence on Random Neighborhood Graphs., , and . J. Mach. Learn. Res., (2007)