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JMLR
2010
155views more  JMLR 2010»
10 years 8 months ago
Structured Sparse Principal Component Analysis
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
Rodolphe Jenatton, Guillaume Obozinski, Francis Ba...
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
10 years 12 months ago
Sparse Unsupervised Dimensionality Reduction Algorithms
Abstract. Principal component analysis (PCA) and its dual—principal coordinate analysis (PCO)—are widely applied to unsupervised dimensionality reduction. In this paper, we sho...
Wenjun Dou, Guang Dai, Congfu Xu, Zhihua Zhang
CORR
2007
Springer
198views Education» more  CORR 2007»
11 years 1 months ago
Clustering and Feature Selection using Sparse Principal Component Analysis
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
Ronny Luss, Alexandre d'Aspremont
NIPS
2008
11 years 2 months ago
Deflation Methods for Sparse PCA
In analogy to the PCA setting, the sparse PCA problem is often solved by iteratively alternating between two subtasks: cardinality-constrained rank-one variance maximization and m...
Lester Mackey
ICCV
2001
IEEE
12 years 3 months ago
Sparse PCA: Extracting Multi-scale Structure from Data
Chakra Chennubhotla, Allan D. Jepson
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