Search for tag: "p.c.a"

ORIE 9000 Colloquium - Madeleine Udell:… duration 1 hour 5 minutes ORIE 9000 Colloquium - Madeleine Udell:… ORIE 9000 Colloquium - Madeleine Udell: Generalized Low Rank Models	ORIE 9000 Colloquium - Madeleine Udell: Generalized Low Rank Models Principal components analysis (PCA) is a well-known technique for approximating a data set represented by a matrix by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets… optimization algorithms and methods +79 More From E. Cornelius 7 plays
ORIE Colloquium, 2014-05-02 - Philippe Rigollet:… duration 1 hour 0 minutes ORIE Colloquium, 2014-05-02 - Philippe Rigollet:… ORIE Colloquium, 2014-05-02 - Philippe Rigollet: The Statistical Price to Pay for Computational Efficiency in Sparse PCA	ORIE Colloquium, 2014-05-02 - Philippe Rigollet: The Statistical Price to Pay for Computational Efficiency in Sparse PCA Friday, May 2 2:20 p.m. – Presentation – 253 Rhodes Hall Philippe Rigollet The statistical price to pay for computational efficiency in sparse PCA Computational limitations of… sigma hat +80 More From E. Cornelius 63 plays

ORIE 9000 Colloquium - Madeleine Udell: Generalized Low Rank Models