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» Dimensionality reduction techniques for proximity problems
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CVPR
2006
IEEE
15 years 11 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»
15 years 3 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
14 years 4 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
15 years 11 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
77
Voted
ECCV
2006
Springer
15 years 11 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