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KDD
2012
ACM
235views Data Mining» more  KDD 2012»
11 years 6 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
IS
2006
13 years 4 months ago
High dimensional nearest neighbor searching
As databases increasingly integrate different types of information such as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of mult...
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agr...
CVPR
2004
IEEE
14 years 6 months ago
Unsupervised Learning of Image Manifolds by Semidefinite Programming
Can we detect low dimensional structure in high dimensional data sets of images? In this paper, we propose an algorithm for unsupervised learning of image manifolds by semidefinit...
Kilian Q. Weinberger, Lawrence K. Saul