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NIPS
2008
8 years 10 months ago
Supervised Exponential Family Principal Component Analysis via Convex Optimization
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
Yuhong Guo
ICASSP
2009
IEEE
9 years 4 months ago
An information geometric approach to supervised dimensionality reduction
Due to the curse of dimensionality, high-dimensional data is often pre-processed with some form of dimensionality reduction for the classiļ¬cation task. Many common methods of su...
Kevin M. Carter, Raviv Raich, Alfred O. Hero
ICML
2008
IEEE
9 years 10 months ago
Closed-form supervised dimensionality reduction with generalized linear models
Irina Rish, Genady Grabarnik, Guillermo Cecchi, Fr...
CVPR
2008
IEEE
9 years 11 months ago
A unified framework for generalized Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
Shuiwang Ji, Jieping Ye
CVPR
2007
IEEE
9 years 11 months ago
Optimal Dimensionality Discriminant Analysis and Its Application to Image Recognition
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
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