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» Dimensionality Reduction with Image Data
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MM
2005
ACM
171views Multimedia» more  MM 2005»
15 years 3 months ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen
ICPR
2004
IEEE
15 years 11 months ago
Nearest Neighbor Ensemble
Recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. The individual predictors (weak learners) can be very simple, ...
Bojun Yan, Carlotta Domeniconi
CVPR
2007
IEEE
15 years 4 months ago
Conformal Embedding Analysis with Local Graph Modeling on the Unit Hypersphere
We present the Conformal Embedding Analysis (CEA) for feature extraction and dimensionality reduction. Incorporating both conformal mapping and discriminating analysis, CEA projec...
Yun Fu, Ming Liu, Thomas S. Huang
NIPS
2007
14 years 11 months ago
Colored Maximum Variance Unfolding
Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...
PAA
2008
14 years 10 months ago
Distance-based discriminant analysis method and its applications
This paper proposes a method of finding a discriminative linear transformation that enhances the data's degree of conformance to the compactness hypothesis and its inverse. Th...
Serhiy Kosinov, Thierry Pun