NeurIPS 2010

Robust PCA via Outlier Pursuit

NeurIPS 2010 hoonose/robust-filter

Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it is nevertheless plagued by a well-known, well-documented sensitivity to outliers.

DIMENSIONALITY REDUCTION MATRIX COMPLETION

An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA

NeurIPS 2010 tbuehler/sparsePCA

Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems.