Michael P Friedlander

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Ewout van den BergIBM T.J. Watson Research CenterVerified email at us.ibm.com
Mark SchmidtAssociate Professor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Felix J. HerrmannProfessor Schools of Earth and Atmospheric Sciences, Computational Science and EngineeringVerified email at gatech.edu
Aleksandr AravkinUniversity of WashingtonVerified email at uw.edu
Ozgur YilmazProfessor, Mathematics, University of British ColumbiaVerified email at math.ubc.ca
Michael SaundersProfessor of Operations Research, Stanford UniversityVerified email at stanford.edu
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Rayan SaabAssociate Professor of Mathematics, UC San DiegoVerified email at ucsd.edu
Gilles Hennenfent, Ph.D.Earth Scientist - ChevronVerified email at chevron.com
James V BurkeUniversity of WashingtonVerified email at uw.edu
Maya GuptaResearcher, Google Research (Formerly Prof. at Univ. Washington)Verified email at google.com
Gabriel GohOpenAIVerified email at openai.com
Stefan ScholtesUniversity of CambridgeVerified email at jbs.cam.ac.uk
Ives MacedoAmazonVerified email at amazon.com
Dominique OrbanProfessor of Computational Mathematics, GERAD and Ecole Polytechnique de MontrealVerified email at gerad.ca
Tristan van LeeuwenCentrum Wiskunde & InformaticaVerified email at cwi.nl
Ting Kei Pong (龐鼎基)Associate Professor, the Hong Kong Polytechnic UniversityVerified email at polyu.edu.hk
Hassan MansourMitsubishi Electric Research LaboratoriesVerified email at merl.com
Dmitriy DrusvyatskiyUniversity of WashingtonVerified email at uw.edu
Andrew CotterGoogle ResearchVerified email at google.com

Michael P Friedlander

Professor of Computer Science and Mathematics, University of British Columbia

Verified email at cs.ubc.ca - Homepage

optimization convex optimization mathematical programming computational mathematics


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Probing the Pareto frontier for basis pursuit solutions E van den Berg, MP Friedlander SIAM Journal on Scientific Computing 31 (2), 890-912, 2008	1983	2008
SPGL1: A solver for large-scale sparse reconstruction E van den Berg, MP Friedlander https://friedlander.io/spgl1/, 2007	497	2007
Hybrid deterministic-stochastic methods for data fitting MP Friedlander, M Schmidt SIAM Journal on Scientific Computing 34 (3), A1380-A1405, 2012	291	2012
Optimizing costly functions with simple constraints: A limited-memory projected quasi-Newton algorithm M Schmidt, E van den Berg, MP Friedlander, K Murphy Artificial Intelligence and Statistics, 456-463, 2009	268	2009
Sparse optimization with least-squares constraints E van den Berg, MP Friedlander SIAM Journal on Optimization 21 (4), 1201-1229, 2011	226	2011
Recovering compressively sampled signals using partial support information MP Friedlander, H Mansour, R Saab, Ö Yilmaz IEEE Transactions on Information Theory 58 (2), 1122-1134, 2011	215	2011
Coordinate descent converges faster with the Gauss-Southwell rule than random selection J Nutini, M Schmidt, I Laradji, MP Friedlander, H Koepke International Conference on Machine Learning, 1632-1641, 2015	175	2015
Theoretical and empirical results for recovery from multiple measurements E van den Berg, MP Friedlander IEEE Transactions on Information Theory 56 (5), 2516-2527, 2010	130	2010
A two-sided relaxation scheme for mathematical programs with equilibrium constraints V DeMiguel, MP Friedlander, FJ Nogales, S Scholtes SIAM Journal on Optimization 16 (2), 587-609, 2005	120*	2005
Satisfying real-world goals with dataset constraints G Goh, A Cotter, M Gupta, M Friedlander arXiv preprint arXiv:1606.07558, 2016	113	2016
Exact regularization of convex programs MP Friedlander, P Tseng SIAM Journal on Optimization 18 (4), 1326-1350, 2008	113	2008
Fighting the curse of dimensionality: Compressive sensing in exploration seismology FJ Herrmann, MP Friedlander, O Yilmaz IEEE Signal Processing Magazine 29 (3), 88-100, 2012	112	2012
Group sparsity via linear-time projection E van den Berg, M Schmidt, MP Friedlander, K Murphy Dept. Comput. Sci., Univ. British Columbia, Vancouver, BC, Canada, 2008	98	2008
Computing non-negative tensor factorizations MP Friedlander, K Hatz Optimisation Methods and Software 23 (4), 631-647, 2008	92	2008
Sparco: A testing framework for sparse reconstruction E van den Berg, MP Friedlander, G Hennenfent, F Herrmann, R Saab, ... Dept. Comput. Sci., Univ. British Columbia, Vancouver, Tech. Rep. TR-2007-20 …, 2007	78	2007
New insights into one-norm solvers from the Pareto curve G Hennenfent, E Berg, MP Friedlander, FJ Herrmann Geophysics 73 (4), A23-A26, 2008	74	2008
Robust inversion, dimensionality reduction, and randomized sampling A Aravkin, MP Friedlander, FJ Herrmann, T Van Leeuwen Mathematical Programming 134 (1), 101-125, 2012	68	2012
Joint-sparse recovery from multiple measurements E Berg, MP Friedlander arXiv preprint arXiv:0904.2051, 2009	67	2009
A globally convergent linearly constrained Lagrangian method for nonlinear optimization MP Friedlander, MA Saunders SIAM Journal on Optimization 15 (3), 863-897, 2005	65	2005
A primal–dual regularized interior-point method for convex quadratic programs MP Friedlander, D Orban Mathematical Programming Computation 4 (1), 71-107, 2012	64	2012

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