Tropp, Joel A

(orcid 0000-0003-1024-1791)

Article(s) from CaltechAUTHORS

• Tropp, Joel A. (2022) Randomized block Krylov methods for approximating extreme eigenvalues Numerische Mathematik; Vol. 150; No. 1; https://doi.org/10.1007/s00211-021-01250-3

• Ding, Lijun; Yurtsever, Alp et al. (2021) An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity SIAM Journal of Optimization; Vol. 31; No. 4; https://doi.org/10.1137/19m1244603

• Huang, De; Niles-Weed, Jonathan et al. (2021) Matrix Concentration for Products Foundations of Computational Mathematics; https://doi.org/10.1007/s10208-021-09533-9 (In Press)

• Huang, De; Tropp, Joel A. (2021) From Poincaré inequalities to nonlinear matrix concentration Bernoulli; Vol. 27; No. 3; https://doi.org/10.3150/20-BEJ1289

• Huang, De; Tropp, Joel A. (2021) Nonlinear matrix concentration via semigroup methods Electronic Journal of Probability; Vol. 26; https://doi.org/10.1214/20-EJP578

• Guta, M.; Kahn, J. et al. (2020) Fast state tomography with optimal error bounds Journal of Physics A: Mathematical and General; Vol. 53; No. 20; https://doi.org/10.1088/1751-8121/ab8111

• Martinsson, Per-Gunnar; Tropp, Joel A. (2020) Randomized numerical linear algebra: Foundations and algorithms Acta Numerica; Vol. 29; https://doi.org/10.1017/s0962492920000021

• Tropp, Joel A.; Yurtsever, Alp et al. (2019) Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation SIAM Journal on Scientific Computing; Vol. 41; No. 4; https://doi.org/10.1137/18m1201068

• Tropp, Joel A. (2018) Simplicial Faces of the Set of Correlation Matrices Discrete and Computational Geometry; Vol. 60; No. 2; https://doi.org/10.1007/s00454-017-9961-0

• Tropp, Joel A.; Yurtsever, Alp et al. (2017) Practical Sketching Algorithms for Low-Rank Matrix Approximation SIAM Journal on Matrix Analysis and Applications; Vol. 38; No. 4; https://doi.org/10.1137/17M1111590

• Tropp, Joel A. (2017) A mathematical introduction to compressive sensing [Book Review] Bulletin of the American Mathematical Society; Vol. 54; No. 1; https://doi.org/10.1090/bull/1546

• Paulin, Daniel; Mackey, Lester et al. (2016) Efron–Stein inequalities for random matrices Annals of Probability; Vol. 44; No. 5; https://doi.org/10.1214/15-AOP1054

• Tropp, Joel A. (2015) Integer Factorization of a Positive-Definite Matrix SIAM Journal on Discrete Mathematics; Vol. 29; No. 4; https://doi.org/10.1137/15M1024718

• Bruer, John J.; Tropp, Joel A. et al. (2015) Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost IEEE Journal of Selected Topics in Signal Processing; Vol. 9; No. 4; https://doi.org/10.1109/JSTSP.2015.2400412

• Tropp, Joel A. (2015) An Introduction to Matrix Concentration Inequalities Foundations and Trends in Machine Learning; Vol. 8; No. 1-2; https://doi.org/10.1561/2200000048

• Horstmeyer, Roarke; Chen, Richard Y. et al. (2015) Solving ptychography with a convex relaxation New Journal of Physics; Vol. 17; No. 5; https://doi.org/10.1088/1367-2630/17/5/053044

• Lerman, Gilad; McCoy, Michael B. et al. (2015) Robust Computation of Linear Models by Convex Relaxation Foundations of Computational Mathematics; Vol. 15; No. 2; https://doi.org/10.1007/s10208-014-9221-0

• Amelunxen, Dennis; Lotz, Martin et al. (2014) Living on the edge: phase transitions in convex programs with random data Information and Inference; Vol. 3; No. 3; https://doi.org/10.1093/imaiai/iau005

• McCoy, Michael B.; Tropp, Joel A. (2014) From Steiner Formulas for Cones to Concentration of Intrinsic Volumes Discrete and Computational Geometry; Vol. 51; No. 4; https://doi.org/10.1007/s00454-014-9595-4

• McCoy, Michael B.; Tropp, Joel A. (2014) Sharp Recovery Bounds for Convex Demixing, with Applications Foundations of Computational Mathematics; Vol. 14; No. 3; https://doi.org/10.1007/s10208-014-9191-2

• Moarref, R.; Jovanović, M. R. et al. (2014) A low-order decomposition of turbulent channel flow via resolvent analysis and convex optimization Physics of Fluids; Vol. 26; No. 5; https://doi.org/10.1063/1.4876195

• Mackey, Lester; Jordan, Michael I. et al. (2014) Matrix concentration inequalities via the method of exchangeable pairs Annals of Probability; Vol. 42; No. 3; https://doi.org/10.1214/13-AOP892

• Chen, Richard Y.; Tropp, Joel A. (2014) Subadditivity of matrix φ-entropy and concentration of random matrices Electronic Journal of Probability; Vol. 19; https://doi.org/10.1214/EJP.v19-2964

• Needell, Deanna; Tropp, Joel A. (2014) Paved with good intentions: Analysis of a randomized block Kaczmarz method Linear Algebra and its Applications; Vol. 441; https://doi.org/10.1016/j.laa.2012.12.022

• Bourguignon, J.-L.; Tropp, J. A. et al. (2014) Compact representation of wall-bounded turbulence using compressive sampling Physics of Fluids; Vol. 26; No. 1; https://doi.org/10.1063/1.4862303

• Moarref, Rashad; Sharma, Ati S. et al. (2013) Model-based scaling of the streamwise energy density in high-Reynolds-number turbulent channels Journal of Fluid Mechanics; Vol. 734; https://doi.org/10.1017/jfm.2013.457

• Pfander, Götz E.; Rauhut, Holger et al. (2013) The restricted isometry property for time-frequency structured random matrices Probability Theory and Related Fields; Vol. 156; No. 3-4; https://doi.org/10.1007/s00440-012-0441-4

• Tropp, Joel A. (2012) A comparison principle for functions of a uniformly random subspace Probability Theory and Related Fields; Vol. 153; No. 3-4; https://doi.org/10.1007/s00440-011-0360-9

• Tropp, Joel A. (2012) User-Friendly Tail Bounds for Sums of Random Matrices Foundations of Computational Mathematics; Vol. 12; No. 4; https://doi.org/10.1007/s10208-011-9099-z

• Tropp, Joel A. (2012) From joint convexity of quantum relative entropy to a concavity theorem of Lieb Proceedings of the American Mathematical Society; Vol. 140; No. 5; https://doi.org/10.1090/S0002-9939-2011-11141-9

• Rauhut, Holger; Romberg, Justin et al. (2012) Restricted isometries for partial random circulant matrices Applied and Computational Harmonic Analysis; Vol. 32; No. 2; https://doi.org/10.1016/j.acha.2011.05.001

• Tropp, Joel A. (2011) Freedman's inequality for matrix martingales Electronic Communications in Probability; Vol. 16; https://doi.org/10.1214/ECP.v16-1624

• Tropp, Joel A. (2011) Freedman’s Inequality for Matrix Martingales Electronic Communications in Probability; Vol. 16; No. 25; https://doi.org/10.1214/ECP.v16-1624

• Tropp, Joel A. (2011) Improved analysis of the subsampled randomized Hadamard transform Advances in Adaptive Data Analysis; Vol. 3; No. 1-2; https://doi.org/10.1142/S1793536911000787

• Halko, N.; Martinsson, P. G. et al. (2011) Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions SIAM Review; Vol. 53; No. 2; https://doi.org/10.1137/090771806

• Tropp, Joel A. (2011) Improved Analysis of the Subsamples Randomized Hadamard Transform Advances in Adaptive Data Analysis; Vol. 3; No. 1-2; https://doi.org/10.1142/S1793536911000787

• McCoy, Michael; Tropp, Joel A. (2011) Two proposals for robust PCA using semidefinite programming Electronic Journal of Statistics; Vol. 5; https://doi.org/10.1214/11-EJS636

• Needell, Deanna; Tropp, Joel A. (2010) CoSaMP: iterative signal recovery from incomplete and inaccurate samples Communications of the ACM; Vol. 53; No. 12; https://doi.org/10.1145/1859204.1859229

• Tropp, Joel A.; Wright, Stephen J. (2010) Computational Methods for Sparse Solution of Linear Inverse Problems Proceedings of the IEEE; Vol. 98; No. 6; https://doi.org/10.1109/JPROC.2010.2044010

• Tropp, Joel A.; Laska, Jason N. et al. (2010) Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals IEEE Transactions on Information Theory; Vol. 56; No. 1; https://doi.org/10.1109/TIT.2009.2034811

• Needell, D.; Tropp, J. A. (2009) CoSaMP: Iterative signal recovery from incomplete and inaccurate samples Applied and Computational Harmonic Analysis; Vol. 26; No. 3; https://doi.org/10.1016/j.acha.2008.07.002

• Tropp, Joel A. (2008) Norms of random submatrices and sparse approximation Comptes Rendus Mathematique; Vol. 346; No. 23-24; https://doi.org/10.1016/j.crma.2008.10.008

• Tropp, Joel A. (2008) On the Linear Independence of Spikes and Sines Journal of Fourier Analysis and Applications; Vol. 14; No. 5-6; https://doi.org/10.1007/s00041-008-9042-0

• Brickell, Justin; Dhillon, Inderjit S. et al. (2008) The Metric Nearness Problem SIAM Journal on Matrix Analysis and Applications; Vol. 30; No. 1; https://doi.org/10.1137/060653391

• Gilnert, Anna C.; Strauss, Martin J. et al. (2008) A Tutorial on Fast Fourier Sampling [How to apply it to problems] IEEE Signal Processing Magazine; Vol. 25; No. 2; https://doi.org/10.1109/MSP.2007.915000

• Dhillon, I. S.; Heath, R. W., Jr. et al. (2008) Constructing Packings in Grassmannian Manifolds via Alternating Projection Experimental Mathematics; Vol. 17; No. 1; https://doi.org/10.1080/10586458.2008.10129018

• Tropp, Joel A. (2008) The random paving property for uniformly bounded matrices Studia Mathematica; Vol. 185; No. 1; https://doi.org/10.4064/sm185-1-4

• Tropp, Joel A.; Gilbert, Anna C. (2007) Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit IEEE Transactions on Information Theory; Vol. 53; No. 12; https://doi.org/10.1109/TIT.2007.909108

• Dhillon, Inderjit S.; Tropp, Joel A. (2007) Matrix Nearness Problems with Bregman Divergences SIAM Journal on Matrix Analysis and Applications; Vol. 29; No. 4; https://doi.org/10.1137/060649021

• Tropp, Joel A. (2006) Just relax: convex programming methods for identifying sparse signals in noise IEEE Transactions on Information Theory; Vol. 52; No. 3; https://doi.org/10.1109/TIT.2005.864420

• Dhillon, Inderjit S.; Heath, Robert W., Jr. et al. (2005) Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum SIAM Journal on Matrix Analysis and Applications; Vol. 27; No. 1; https://doi.org/10.1137/S0895479803438183

• Tropp, Joel A. (2005) Recovery of short, complex linear combinations via ℓ1 minimization IEEE Transactions on Information Theory; Vol. 2005; No. 4; https://doi.org/10.1109/TIT.2005.844057

• Tropp, Joel A.; Dhillon, Inderjit S. et al. (2005) Designing structured tight frames via an alternating projection method IEEE Transactions on Information Theory; Vol. 51; No. 1; https://doi.org/10.1109/TIT.2004.839492

• Tropp, Joel A.; Dhillon, Inderjit S. et al. (2004) Finite-step algorithms for constructing optimal CDMA signature sequences IEEE Transactions on Information Theory; Vol. 50; No. 11; https://doi.org/10.1109/TIT.2004.836698

• Tropp, Joel A. (2004) Greed is good: algorithmic results for sparse approximation IEEE Transactions on Information Theory; Vol. 50; No. 10; https://doi.org/10.1109/TIT.2004.834793