Sparse PCA via covariance thresholding

DeshpandeYash; MontanariAndrea

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Sparse PCA via covariance thresholding

DeshpandeYash MontanariAndrea

Year: 2016 Journal: Journal of Machine Learning Research Publisher: The MIT Press

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Abstract

In sparse principal component analysis we are given noisy observations of a low-rank matrix of dimension n × p and seek to reconstruct it under additional sparsity assumptions. In particular, we as...

Keywords:

Principal component analysis Sparse PCA Thresholding Pattern recognition (psychology) Dimension (graph theory) Artificial intelligence Robust principal component analysis Rank (graph theory) Covariance matrix Covariance Computer science Mathematics Matrix (chemical analysis) Algorithm Statistics Combinatorics Image (mathematics)

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Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

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Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Blind Source Separation Techniques

Physical Sciences → Computer Science → Signal Processing

Sparse PCA via covariance thresholding

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