The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data (2000)

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by Andrew W. Moore
Venue:In Twelfth Conference on Uncertainty in Artificial Intelligence
Citations:86 - 9 self

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The Anchors Hierarchy: Using the triangle – Andrew W. Moore, Andrew W. Moore - 2000
1 Cached Sufficient Statistics for Automated Mining and Discovery from Massive Data Sources – Andrew Moore, Jeff Schneider, Brigham Anderson Brighamcs. Cmu. Edu, Paul Komarek Komarekcs. Cmu. Edu, Remi Munos Munoscs. Clm. Edu, Kary Myers Karycs. Cmu. Edu, Dan Pelleg Dpellegcs. Cmu. Edu - 2000
99 `N-Body' Problems in Statistical Learning – Alexander G. Gray, Andrew W. Moore - 2001
536 A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces – R WEBER, H-J SCHEK, S BOTT - 1998
499 Locally weighted learning – Christopher G. Atkeson, Andrew W. Moore , Stefan Schaal - 1997
673 Automatically characterizing large scale program behavior – Timothy Sherwood, Erez Perelman, Greg Hamerly - 2002
628 Visual categorization with bags of keypoints – Gabriella Csurka, Christopher R. Dance, Lixin Fan, Jutta Willamowski, C├ędric Bray - 2004
754 Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals – Jim Gray, Adam Bosworth, Andrew Layman, Don Reichart, Hamid Pirahesh - 1996
533 Maximizing the Spread of Influence Through a Social Network – David Kempe - 2003