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» Assessing Data Mining Results on Matrices with Randomization
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ACSW
2004
13 years 10 months ago
Early Assessment of Classification Performance
The ability to distinguish between objects is the fundamental to learning and intelligent behavior in general. The difference between two things is the information we seek; the pr...
Bostjan Brumen, Izidor Golob, Hannu Jaakkola, Tatj...
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
11 years 11 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
ICDM
2005
IEEE
125views Data Mining» more  ICDM 2005»
14 years 2 months ago
Alternate Representation of Distance Matrices for Characterization of Protein Structure
The most suitable method for the automated classification of protein structures remains an open problem in computational biology. In order to classify a protein structure with an...
Keith Marsolo, Srinivasan Parthasarathy
SDM
2012
SIAM
245views Data Mining» more  SDM 2012»
11 years 11 months ago
Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study
Low-rank approximations which are computed from selected rows and columns of a given data matrix have attracted considerable attention lately. They have been proposed as an altern...
Christian Thurau, Kristian Kersting, Christian Bau...
CORR
2010
Springer
115views Education» more  CORR 2010»
13 years 7 months ago
Tight oracle bounds for low-rank matrix recovery from a minimal number of random measurements
This paper presents several novel theoretical results regarding the recovery of a low-rank matrix from just a few measurements consisting of linear combinations of the matrix entr...
Emmanuel J. Candès, Yaniv Plan