Michael B. McCoy
Michael B. McCoy
Computing and Mathematical Sciences, California Institute of Technology
Verified email at caltech.edu - Homepage
Cited by
Cited by
Living on the edge: Phase transitions in convex programs with random data
D Amelunxen, M Lotz, MB McCoy, JA Tropp
Information and Inference: A Journal of the IMA 3 (3), 224-294, 2014
Two proposals for robust PCA using semidefinite programming
M McCoy, JA Tropp
Electronic Journal of Statistics 5, 1123-1160, 2011
Robust computation of linear models by convex relaxation
G Lerman, MB McCoy, JA Tropp, T Zhang
Foundations of Computational Mathematics 15 (2), 363-410, 2015
Sharp recovery bounds for convex demixing, with applications
MB McCoy, JA Tropp
Foundations of Computational Mathematics 14, 503-567, 2014
Convexity in source separation: Models, geometry, and algorithms
MB McCoy, V Cevher, QT Dinh, A Asaei, L Baldassarre
IEEE Signal Processing Magazine 31 (3), 87-95, 2014
From Steiner formulas for cones to concentration of intrinsic volumes
MB McCoy, JA Tropp
Discrete & Computational Geometry 51 (4), 926-963, 2014
The achievable performance of convex demixing
MB McCoy, JA Tropp
arXiv preprint arXiv:1309.7478, 2013
A geometric analysis of convex demixing
MB McCoy
California Institute of Technology, 2013
Concentration of the intrinsic volumes of a convex body
M Lotz, MB McCoy, I Nourdin, G Peccati, JA Tropp
Geometric Aspects of Functional Analysis, 139-167, 2020
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