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CIKM
2000
Springer
13 years 10 months ago
Dimensionality Reduction and Similarity Computation by Inner Product Approximations
—As databases increasingly integrate different types of information such as multimedia, spatial, time-series, and scientific data, it becomes necessary to support efficient retri...
Ömer Egecioglu, Hakan Ferhatosmanoglu
PAMI
2011
13 years 28 days 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
ICPR
2008
IEEE
14 years 13 days ago
Learning a discriminative sparse tri-value transform
Simple binary patterns have been successfully used for extracting feature representations for visual object classification. In this paper, we present a method to learn a set of d...
Zhenhua Qu, Guoping Qiu, Pong Chi Yuen
CVPR
2004
IEEE
14 years 8 months ago
Unsupervised Learning of Image Manifolds by Semidefinite Programming
Can we detect low dimensional structure in high dimensional data sets of images? In this paper, we propose an algorithm for unsupervised learning of image manifolds by semidefinit...
Kilian Q. Weinberger, Lawrence K. Saul
NIPS
2008
13 years 7 months ago
MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features
We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-c...
Tae-Kyun Kim, Roberto Cipolla