# Approximation Bounds for Sparse Principal Component Analysis

Friday, February 8, 2013 -

4:30pm to 5:30pm

We produce approximation bounds on a semidefinite programming relaxation for sparse principal component analysis. These bounds control approximation ratios for tractable statistics in hypothesis testing problems where data points are sampled from Gaussian models with a single sparse leading component.

Speaker:

Alexandre d'Aspremont

CMAP-Ecole Polytechnique

Event Location:

Fine Hall 214