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…

Tuesday, May 6, 2014 at 4:15 PM [.ics]
253 Rhodes Hall
Alexander (Sasha) Rakhlin
Assistant Professor, Department of Statistics
Secondary appointment: Department of Computer & Information…

Motivated by the availability of real-time data on customer characteristics, we consider the problem of personalizing the assortment of products for each arriving customer. Using actual sales data…

ORIE Special Seminar: Shuangchi He (National University of Singapore) - A One-Dimensional Diffusion Model for Overloaded Queues with Customer Abandonment
Tuesday, April 9, 2013 at 4:15pm
Frank H.…

ORIE Colloquium: Marco Molinaro (Carnegie Mellon) - Incomplete Information and Large Dimensionality in Decision Making
Tuesday, February 26, 2013 at 4:15pm
Frank H. T. Rhodes Hall, 253
This talk…