Joel Tropp | Academic Influence

Joel Tropp's AcademicInfluence.com Rankings

Joel Tropp

Mathematics

#2816

World Rank

#4270

Historical Rank

#1088

USA Rank

Applied Mathematics

#76

World Rank

#88

Historical Rank

#40

USA Rank

Measure Theory

#729

World Rank

#982

Historical Rank

#292

USA Rank

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Mathematics

Joel Tropp's Degrees

PhD Applied Mathematics California Institute of Technology
Bachelors Mathematics Stanford University

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Why Is Joel Tropp Influential?

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According to Wikipedia, Joel Aaron Tropp is the Steele Family Professor of Applied and Computational Mathematics in the Computing and Mathematical Sciences Department at the California Institute of Technology. He is known for work on sparse approximation, numerical linear algebra, and random matrix theory.

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Joel Tropp's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit (2007) (8531)
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples (2008) (4576)
Greed is good: algorithmic results for sparse approximation (2004) (3635)
Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions (2009) (3466)
User-Friendly Tail Bounds for Sums of Random Matrices (2010) (1560)
Just relax: convex programming methods for identifying sparse signals in noise (2006) (1435)
Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit (2006) (1322)
Computational Methods for Sparse Solution of Linear Inverse Problems (2010) (1125)
Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals (2009) (1054)
An Introduction to Matrix Concentration Inequalities (2015) (912)
Algorithms for simultaneous sparse approximation. Part II: Convex relaxation (2006) (791)
ALGORITHMS FOR SIMULTANEOUS SPARSE APPROXIMATION (2006) (568)
SIGNAL RECOVERY FROM PARTIAL INFORMATION VIA ORTHOGONAL MATCHING PURSUIT (2005) (566)
Living on the edge: phase transitions in convex programs with random data (2013) (453)
Designing structured tight frames via an alternating projection method (2005) (447)
One sketch for all: fast algorithms for compressed sensing (2007) (310)
Random Filters for Compressive Sampling and Reconstruction (2006) (309)
Improved Analysis of the subsampled Randomized Hadamard Transform (2010) (289)
Simultaneous sparse approximation via greedy pursuit (2005) (280)
On the existence of equiangular tight frames (2007) (232)
On the conditioning of random subdictionaries (2008) (225)
Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method (2012) (220)
Factoring nonnegative matrices with linear programs (2012) (212)
Restricted Isometries for Partial Random Circulant Matrices (2010) (209)
JUST RELAX: CONVEX PROGRAMMING METHODS FOR SUBSET SELECTION AND SPARSE APPROXIMATION (2004) (198)
JUST RELAX: CONVEX PROGRAMMING METHODS FOR SUBSET SELECTION AND SPARSE APPROXIMATION (2004) (198)
FREEDMAN'S INEQUALITY FOR MATRIX MARTINGALES (2011) (169)
Matrix Nearness Problems with Bregman Divergences (2007) (169)
Two proposals for robust PCA using semidefinite programming (2010) (164)
Algorithmic linear dimension reduction in the l_1 norm for sparse vectors (2006) (160)
Convex recovery of a structured signal from independent random linear measurements (2014) (160)
Practical Large-Scale Optimization for Max-norm Regularization (2010) (159)
Matrix concentration inequalities via the method of exchangeable pairs (2012) (153)
Constructing Packings in Grassmannian Manifolds via Alternating Projection (2007) (152)
Topics in sparse approximation (2004) (150)
Sparse Approximation Via Iterative Thresholding (2006) (150)
Practical Sketching Algorithms for Low-Rank Matrix Approximation (2016) (146)
Robust Computation of Linear Models by Convex Relaxation (2012) (134)
Column subset selection, matrix factorization, and eigenvalue optimization (2008) (120)
Model-based scaling of the streamwise energy density in high-Reynolds-number turbulent channels (2013) (118)
A Tutorial on Fast Fourier Sampling (2008) (116)
Living on the edge: A geometric theory of phase transitions in convex optimization (2013) (109)
Randomized numerical linear algebra: Foundations and algorithms (2020) (108)
Greedy signal recovery review (2008) (101)
Universality laws for randomized dimension reduction, with applications (2015) (99)
Sharp Recovery Bounds for Convex Demixing, with Applications (2012) (97)
Solving ptychography with a convex relaxation (2014) (91)
Recovery of short, complex linear combinations via /spl lscr//sub 1/ minimization (2005) (88)
User-Friendly Tools for Random Matrices: An Introduction (2012) (83)
Norms of Random Submatrices and Sparse Approximation (2008) (82)
Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage (2017) (80)
Finite-step algorithms for constructing optimal CDMA signature sequences (2004) (77)
Scalable Semidefinite Programming (2019) (74)
Improved sparse approximation over quasiincoherent dictionaries (2003) (68)
The restricted isometry property for time–frequency structured random matrices (2011) (66)
Fast state tomography with optimal error bounds (2018) (62)
Recovery of short, complex linear combinations via 𝓁1 minimization (2005) (61)
A low-order decomposition of turbulent channel flow via resolvent analysis and convex optimization (2014) (59)
Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation (2019) (59)
The Masked Sample Covariance Estimator: An Analysis via Matrix Concentration Inequalities (2011) (58)
Efficient sampling of sparse wideband analog signals (2008) (56)
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data (2017) (55)
Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum (2005) (54)
The Metric Nearness Problem (2008) (53)
Robust computation of linear models, or How to find a needle in a haystack (2012) (53)
From Steiner Formulas for Cones to Concentration of Intrinsic Volumes (2013) (51)
The achievable performance of convex demixing (2013) (50)
TAIL BOUNDS FOR ALL EIGENVALUES OF A SUM OF RANDOM MATRICES (2011) (50)
Randomized Numerical Linear Algebra: Foundations & Algorithms (2020) (49)
Low-Rank Tucker Approximation of a Tensor From Streaming Data (2019) (49)
The Expected Norm of a Sum of Independent Random Matrices: An Elementary Approach (2015) (47)
On the Linear Independence of Spikes and Sines (2007) (46)
User-Friendly Tail Bounds for Matrix Martingales (2011) (45)
The random paving property for uniformly bounded matrices (2006) (38)
Subadditivity of Matrix phi-Entropy and Concentration of Random Matrices (2013) (37)
Sharp recovery bounds for convex deconvolution, with applications (2012) (37)
From joint convexity of quantum relative entropy to a concavity theorem of Lieb (2011) (36)
Efron–Stein inequalities for random matrices (2014) (33)
Complex equiangular tight frames (2005) (31)
Randomized single-view algorithms for low-rank matrix approximation (2016) (31)
Applications of sparse approximation in communications (2005) (30)
CoSaMP (2010) (29)
Matrix Concentration for Products (2020) (28)
Tensor Random Projection for Low Memory Dimension Reduction (2021) (27)
An Optimal-Storage Approach to Semidefinite Programming using Approximate Complementarity (2019) (27)
CDMA signature sequences with low peak-to-average-power ratio via alternating projection (2003) (27)
Error Bounds for Random Matrix Approximation Schemes (2009) (25)
Second-Order Matrix Concentration Inequalities (2015) (22)
Open Problems in Data Streams, Property Testing, and Related Topics (2011) (21)
Compact representation of wall-bounded turbulence using compressive sampling (2014) (21)
Quantum simulation via randomized product formulas: Low gate complexity with accuracy guarantees (2020) (20)
Triangle Fixing Algorithms for the Metric Nearness Problem (2004) (20)
Concentration for Random Product Formulas (2020) (20)
The sparsity gap: Uncertainty principles proportional to dimension (2010) (20)
Row-Action Methods for Compressed Sensing (2006) (18)
Topics in randomized numerical linear algebra (2013) (17)
Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost (2015) (17)
Random Filters for Compressive Sampling (2006) (16)
Average-case analysis of greedy pursuit (2005) (15)
User-Friendly Tail Bounds for Sums of Random Matrices (2011) (15)
Deriving Matrix Concentration Inequalities from Kernel Couplings (2013) (14)
Corrigendum in “Just Relax: Convex Programming Methods for Identifying Sparse Signals in Noise” [Mar 06 1030-1051] (2009) (14)
Literature Survey : Non-Negative Matrix Factorization (2003) (13)
Randomized Nyström Preconditioning (2021) (13)
Concentration of the Intrinsic Volumes of a Convex Body (2018) (13)
Time-Data Tradeoffs by Aggressive Smoothing (2014) (13)
The Masked Sample Covariance Estimator: An Analysis via the Matrix Laplace Transform (2012) (12)
A comparison principle for functions of a uniformly random subspace (2011) (11)
Simplicial Faces of the Set of Correlation Matrices (2018) (11)
Construction of equiangular signatures for synchronous CDMA systems (2004) (9)
Binary Component Decomposition Part I: The Positive-Semidefinite Case (2019) (9)
Nonlinear matrix concentration via semigroup methods (2020) (9)
Fast & Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems (2021) (8)
AN ALTERNATING MINIMIZATION ALGORITHM FOR NON-NEGATIVE MATRIX APPROXIMATION (2003) (8)
Optimal CDMA signature sequences, inverse eigenvalue problems and alternating minimization (2003) (7)
Binary component decomposition Part II: The asymmetric case (2019) (7)
From Poincaré inequalities to nonlinear matrix concentration (2020) (6)
Matrix Concentration & Computational Linear Algebra (2019) (6)
Book Review: A mathematical introduction to compressive sensing (2016) (6)
Learning to Forecast Dynamical Systems from Streaming Data (2021) (5)
Sublinear approximation of signals (2006) (5)
Randomized block Krylov methods for approximating extreme eigenvalues (2021) (4)
Inference of Black Hole Fluid-Dynamics from Sparse Interferometric Measurements (2021) (4)
AN ELEMENTARY PROOF OF THE SPECTRAL RADIUS FORMULA FOR (4)
Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations (2022) (3)
A foundation for analytical developments in the logarithmic region of turbulent channels (2014) (3)
Integer Factorization of a Positive-Definite Matrix (2015) (2)
Jackknife Variability Estimation For Randomized Matrix Computations (2022) (2)
The Metric Nearness Problem with Applications (2003) (2)
Randomized Nystr\"om Preconditioning (2021) (2)
Optimal CDMA signatures: a finite-step approach (2004) (2)
On effectiveness of a rank-1 model of turbulent channels for representing the velocity spectra (2013) (2)
Sketchy decisions: convex optimization with optimal storage (Conference Presentation) (2017) (2)
CONSTRUCTING PACKINGS IN PROJECTIVE SPACES AND GRASSMANNIAN SPACES VIA ALTERNATING PROJECTION (2004) (2)
LARGE-SCALE PCA WITH SPARSITY CONSTRAINTS (2011) (1)
XTrace: Making the most of every sample in stochastic trace estimation (2023) (1)
The restricted isometry property for time–frequency structured random matrices (2012) (1)
Infinitesimals : History & Application (1)
A faster fourier transform: A mathematical upgrade promises a speedier digital world (2012) (1)
Sparse random Hamiltonians are quantumly easy (2023) (1)
Sharp phase transitions in Euclidean integral geometry (2022) (1)
Simplicial Faces of the Set of Correlation Matrices (2018) (0)
FLOW AROUND A SYMMETRIC OBSTACLE (0)
Wall Turbulence with Designer Properties: Identification, Characterization and Manipulation of Energy Pathways (2016) (0)
United States Patent Baraniuk (2012) (0)
Applied Random Matrix Theory (2018) (0)
ON GEOMETRICALLY SELF-SIMILAR MODES IN WALL-BOUNDED TURBULENT FLOWS (2013) (0)
From Steiner Formulas for Cones to Concentration of Intrinsic Volumes (2014) (0)
Randomized block Krylov methods for approximating extreme eigenvalues (2021) (0)
Representation of the velocity spectra and Reynolds stress co-spectrum in turbulent channel flow using resolvent modes (2013) (0)
CNOIDAL SOLUTIONS TO THE pTH-ORDER KORTEWEG-DE VRIES EQUATION (0)
N A ] 1 1 D ec 2 00 8 GREEDY SIGNAL RECOVERY REVIEW (2018) (0)
A ug 2 01 4 Efron – Stein Inequalities for Random Matrices (2014) (0)
Nonlinear interactions and their scaling in the logarithmic region of turbulent channels (2014) (0)
A comparison principle for functions of a uniformly random subspace (2011) (0)
Model-based scaling and prediction of streamwise energy spectrum at high Reynolds numbers (2012) (0)
The paving property for uniformly bounded matrices: A new proof (2006) (0)
GALERKIN ’ S METHOD FOR NONLINEAR COMPACT FIXED-POINT PROBLEMS (0)
Robust Computation of Linear Models by Convex Relaxation (2014) (0)
The paving property for uniformly bounded matrices (2006) (0)
Robust, randomized preconditioning for kernel ridge regression (2023) (0)
SOLVING PTYCHOGRAPHY WITH A CONVEX RELAXATION : SUPPLEMENTARY MATERIAL (2015) (0)
Sharp Recovery Bounds for Convex Demixing, with Applications (2014) (0)
VIA THE METHOD OF EXCHANGEABLE PAIRS (2013) (0)
Information Dynamics as Foundation for Network Management (2014) (0)
Sparse and Low Rank Approximation ( 11 w 5036 ) (2011) (0)
Integer representation of a positive-definite matrix (2015) (0)
Technical Report No . 201 702 February 201 7 THE ACHIEVABLE PERFORMANCE OF CONVEX DEMIXING (2013) (0)
The Bowling Scheme (2014) (0)
Efficient error and variance estimation for randomized matrix computations (2022) (0)
Uncertainty Principles meet Linear Algebra (2006) (0)
Metric Nearness : Problem Formulation and Algorithms (0)
Time – Data Tradeo ff s by Aggressive Smoothing (2014) (0)

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