Monday February 9
8:00	Coffee and Registration
9:15-9:30	Welcoming Remarks
9:30-10:30	Petros Drineas (via WebEx), Rensselaer Polytechnic Institute RandNLA: Randomization in Numerical Linear Algebra
10:30-11:00	Coffee
11:00-12:00	Alexandre d'Aspremont, École Normale Supérieure
12:00-2:00	Lunch
2:00-3:00	Inderjit S. Dhillon, University of Texas Sparse inverse covariance estimation for a million variables
3:00-3:30	Tea
3:30-4:30	Maryam Fazel, University of Washington Convex regularization with the Diversity norm: properties and algorithms
4:30-5:30	Michael Friedlander, University of California, Davis
5:30	Cash Bar Reception
Tuesday February 10
9:30-10:30	Animashree Anandkumar, University of California, Irvine Spectral Methods for Generative and Discriminative Learning with Latent Variables
10:30-11:00	Coffee break
11:00-12:00	Lin Xiao, Microsoft Research Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss
12:00-2:00	Lunch break
2:00-3:00	Ben Recht (via WebEx), University of California, Berkeley
3:00-3:30	Tea break
3:30-4:30	Tamara Kolda, Sandia National Laboratories Computing the Largest Entries in a Matrix Product via Sampling
4:30-5:30	Yaniv Plan, University of British Columbia The generalized lasso with non-linear measurements
Wednesday February 11
9:30-10:30	Michael Mahoney, University of California, Berkeley Eigenvector localization, implicit regularization, and algorithmic anti-differentiation for large-scale graphs and matrix data
10:30-11:00	Coffee break
11:00-12:00	Quentin Berthet, California Institute of Technology Statistical and Computational Tradeoffs for Sparse Principal Component Analysis
12:00-1:00	Lunch break (On-site lunch)
1:00-2:00	Po-Ling Loh, University of Pennsylvania PDW methods for support recovery in nonconvex high-dimensional problems
2:00-3:00	Jakub Marecek, IBM Research Coordinate Descent and Challenges therein
3:00-3:30	Tea break
3:30 -4:30	Stephen A. Vavasis, University of Waterloo