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…

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…