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CORR
1999
Springer
222views Education» more  CORR 1999»
15 years 6 months ago
Analysis of approximate nearest neighbor searching with clustered point sets
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
Songrit Maneewongvatana, David M. Mount
CVPR
2006
IEEE
16 years 8 months ago
Unsupervised Bayesian Detection of Independent Motion in Crowds
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
Gabriel J. Brostow, Roberto Cipolla
ICML
2004
IEEE
16 years 7 months ago
Automated hierarchical mixtures of probabilistic principal component analyzers
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
Ting Su, Jennifer G. Dy
NIPS
2000
15 years 8 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
15 years 5 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur