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…
ORIE Colloquium: Guy Lebanon (Georgia Tech) - Stochastic m-Estimators and the Tradeoff Between Statistical Accuracy and Computational Complexity
Tuesday, February 5, 2013 at 4:15pm
Frank H. T.…