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» Dimensionality reduction techniques for proximity problems
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CVPR
2006
IEEE
14 years 9 months ago
Dimensionality Reduction by Learning an Invariant Mapping
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
Raia Hadsell, Sumit Chopra, Yann LeCun
ADC
2006
Springer
158views Database» more  ADC 2006»
14 years 1 months ago
Dimensionality reduction in patch-signature based protein structure matching
Searching bio-chemical structures is becoming an important application domain of information retrieval. This paper introduces a protein structure matching problem and formulates i...
Zi Huang, Xiaofang Zhou, Dawei Song, Peter Bruza
PAMI
2011
13 years 2 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
ECCV
2004
Springer
14 years 9 months ago
Dimensionality Reduction by Canonical Contextual Correlation Projections
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Marco Loog, Bram van Ginneken, Robert P. W. Duin
ECCV
2006
Springer
14 years 9 months ago
Sampling Representative Examples for Dimensionality Reduction and Recognition - Bootstrap Bumping LDA
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
Hui Gao, James W. Davis