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KDD
2001
ACM
203views Data Mining» more  KDD 2001»
16 years 6 days ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
AAAI
2008
15 years 2 months ago
Dimension Amnesic Pyramid Match Kernel
With the success of local features in object recognition, feature-set representations are widely used in computer vision and related domains. Pyramid match kernel (PMK) is an effi...
Yi Liu, Xulei Wang, Hongbin Zha
CSDA
2008
65views more  CSDA 2008»
14 years 12 months ago
On the number of principal components: A test of dimensionality based on measurements of similarity between matrices
An important problem in principal component analysis (PCA) is the estimation of the correct number of components to retain. PCA is most often used to reduce a set of observed vari...
Stéphane Dray
MMM
2011
Springer
251views Multimedia» more  MMM 2011»
14 years 3 months ago
Randomly Projected KD-Trees with Distance Metric Learning for Image Retrieval
Abstract. Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree...
Pengcheng Wu, Steven C. H. Hoi, Duc Dung Nguyen, Y...
102
Voted
CVPR
2010
IEEE
14 years 10 months ago
Transform Coding for Fast Approximate Nearest Neighbor Search in High Dimensions
We examine the problem of large scale nearest neighbor search in high dimensional spaces and propose a new approach based on the close relationship between nearest neighbor search...
Jonathan Brandt