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» Local Dimensionality Reduction
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ICASSP
2011
IEEE
14 years 1 months ago
Compressed classification of observation sets with linear subspace embeddings
We consider the problem of classification of a pattern from multiple compressed observations that are collected in a sensor network. In particular, we exploit the properties of r...
Dorina Thanou, Pascal Frossard
ICPR
2006
IEEE
15 years 10 months ago
Object Tracking Using Globally Coordinated Nonlinear Manifolds
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...
Che-Bin Liu, Ming-Hsuan Yang, Narendra Ahuja, Ruei...
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ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
15 years 1 months ago
Spectral Regression: A Unified Approach for Sparse Subspace Learning
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
Deng Cai, Xiaofei He, Jiawei Han
AAAI
2010
14 years 6 months ago
Multilinear Maximum Distance Embedding Via L1-Norm Optimization
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
Yang Liu, Yan Liu, Keith C. C. Chan
CVPR
2006
IEEE
15 years 11 months ago
Learning Semantic Patterns with Discriminant Localized Binary Projections
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...
Shuicheng Yan, Tianqiang Yuan, Xiaoou Tang