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Michael P. Friedlander, “Algorithms for large-scale sparse reconstruction”, in IEMS, Northwestern University, 2009.
Michael P. Friedlander, “Computing sparse and group-sparse approximations”, in VIET, Hanoi, Vietnam, 2009.
Michael P. Friedlander, “Active-set approaches to basis pursuit denoising”, in SIAM Optimization, 2008.
Michael P. Friedlander, “Algorithms for large-scale sparse reconstruction”, in SINBAD 2008, 2008.
Michael P. Friedlander and M. A. Saunders, “Active-set methods for basis pursuit”, in WCOM, 2008.
Michael P. Friedlander, “Randomized sampling: How confident are you?”, SINBAD Fall consortium talks. SINBAD, 2012.
Michael P. Friedlander, “Robust inversion, data-fitting, and inexact gradient methods”, SINBAD Fall consortium talks. SINBAD, 2011.
Michael P. Friedlander, “Algorithms for sparse optimization”, SINBAD Fall consortium talks. SINBAD, 2010.
Michael P. Friedlander, “Introduction to Spot: a linear-operator toolbox”, SINBAD Fall consortium talks. SINBAD, 2010.
Michael P. Friedlander, Hassan Mansour, Rayan Saab, and Ozgur Yilmaz, “Recovering compressively sampled signals using partial support information”, IEEE Transactions on Information Theory, vol. 58, pp. 1122-1134, 2012.
Michael P. Friedlander and Mark Schmidt, “Hybrid deterministic-stochastic methods for data fitting”, SIAM Journal on Scientific Computing, vol. 34, pp. A1380-A1405, 2012.
Michael P. Friedlander and P. Tseng, “Exact regularization of convex programs”, SIAM Journal on Optimization, vol. 18, pp. 1326-1350, 2007.
Michael P. Friedlander and M. A. Saunders, “Discussion: the Dantzig selector: statistical estimation when p is much larger than n”, The Annals of Statistics, vol. 35, pp. 2385-2391, 2007.