Joel A. Tropp

Orcid: 0000-0003-1024-1791

Affiliations:
  • California Institute of Technology, Pasadena, USA


According to our database1, Joel A. Tropp authored at least 83 papers between 2003 and 2024.

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Bibliography

2024
XTrace: Making the Most of Every Sample in Stochastic Trace Estimation.
SIAM J. Matrix Anal. Appl., March, 2024

Efficient Error and Variance Estimation for Randomized Matrix Computations.
SIAM J. Sci. Comput., February, 2024

Randomized matrix computations: Themes and variations.
CoRR, 2024

2023
Randomized Nyström Preconditioning.
SIAM J. Matrix Anal. Appl., June, 2023

Learning to Forecast Dynamical Systems from Streaming Data.
SIAM J. Appl. Dyn. Syst., June, 2023

Randomized algorithms for low-rank matrix approximation: Design, analysis, and applications.
CoRR, 2023

Robust, randomized preconditioning for kernel ridge regression.
CoRR, 2023

2022
Randomized block Krylov methods for approximating extreme eigenvalues.
Numerische Mathematik, 2022

Matrix Concentration for Products.
Found. Comput. Math., 2022

Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations.
CoRR, 2022

Jackknife Variability Estimation For Randomized Matrix Computations.
CoRR, 2022

2021
Scalable Semidefinite Programming.
SIAM J. Math. Data Sci., 2021

Binary Component Decomposition Part I: The Positive-Semidefinite Case.
SIAM J. Math. Data Sci., 2021

An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity.
SIAM J. Optim., 2021

Fast & Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems.
CoRR, 2021

Learning to Forecast Dynamical Systems from Streaming Data.
CoRR, 2021

Tensor Random Projection for Low Memory Dimension Reduction.
CoRR, 2021

Inference of Black Hole Fluid-Dynamics from Sparse Interferometric Measurements.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Low-Rank Tucker Approximation of a Tensor from Streaming Data.
SIAM J. Math. Data Sci., 2020

Randomized Numerical Linear Algebra: Foundations & Algorithms.
CoRR, 2020

Randomized numerical linear algebra: Foundations and algorithms.
Acta Numer., 2020

2019
Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation.
SIAM J. Sci. Comput., 2019

Binary component decomposition Part II: The asymmetric case.
CoRR, 2019

2018
Simplicial Faces of the Set of Correlation Matrices.
Discret. Comput. Geom., 2018

Concentration of the Intrinsic Volumes of a Convex Body.
CoRR, 2018

Fast state tomography with optimal error bounds.
CoRR, 2018

2017
Practical Sketching Algorithms for Low-Rank Matrix Approximation.
SIAM J. Matrix Anal. Appl., 2017

Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Randomized single-view algorithms for low-rank matrix approximation.
CoRR, 2016

2015
Integer Factorization of a Positive-Definite Matrix.
SIAM J. Discret. Math., 2015

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost.
IEEE J. Sel. Top. Signal Process., 2015

An Introduction to Matrix Concentration Inequalities.
Found. Trends Mach. Learn., 2015

Robust Computation of Linear Models by Convex Relaxation.
Found. Comput. Math., 2015

Universality laws for randomized dimension reduction, with applications.
CoRR, 2015

2014
Sharp Recovery Bounds for Convex Demixing, with Applications.
Found. Comput. Math., 2014

From Steiner Formulas for Cones to Concentration of Intrinsic Volumes.
Discret. Comput. Geom., 2014

Convex recovery of a structured signal from independent random linear measurements.
CoRR, 2014

Time-Data Tradeoffs by Aggressive Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Living on the edge: A geometric theory of phase transitions in convex optimization
CoRR, 2013

Subadditivity of Matrix phi-Entropy and Concentration of Random Matrices.
CoRR, 2013

The achievable performance of convex demixing.
CoRR, 2013

2012
User-Friendly Tail Bounds for Sums of Random Matrices.
Found. Comput. Math., 2012

Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method
CoRR, 2012

Sharp recovery bounds for convex deconvolution, with applications
CoRR, 2012

Robust computation of linear models, or How to find a needle in a haystack
CoRR, 2012

Factoring nonnegative matrices with linear programs.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions.
SIAM Rev., 2011

The restricted isometry property for time-frequency structured random matrices
CoRR, 2011

From joint convexity of quantum relative entropy to a concavity theorem of Lieb
CoRR, 2011

Improved Analysis of the subsampled Randomized Hadamard Transform.
Adv. Data Sci. Adapt. Anal., 2011

2010
Beyond Nyquist: efficient sampling of sparse bandlimited signals.
IEEE Trans. Inf. Theory, 2010

Computational Methods for Sparse Solution of Linear Inverse Problems.
Proc. IEEE, 2010

Restricted Isometries for Partial Random Circulant Matrices
CoRR, 2010

CoSaMP: iterative signal recovery from incomplete and inaccurate samples.
Commun. ACM, 2010

Practical Large-Scale Optimization for Max-norm Regularization.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

The sparsity gap: Uncertainty principles proportional to dimension.
Proceedings of the 44th Annual Conference on Information Sciences and Systems, 2010

2009
Efficient Sampling of Sparse Wideband Analog Signals
CoRR, 2009

Column subset selection, matrix factorization, and eigenvalue optimization.
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

2008
A Tutorial on Fast Fourier Sampling.
IEEE Signal Process. Mag., 2008

The Metric Nearness Problem.
SIAM J. Matrix Anal. Appl., 2008

Constructing Packings in Grassmannian Manifolds via Alternating Projection.
Exp. Math., 2008

Greedy signal recovery review.
Proceedings of the 42nd Asilomar Conference on Signals, Systems and Computers, 2008

2007
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit.
IEEE Trans. Inf. Theory, 2007

Matrix Nearness Problems with Bregman Divergences.
SIAM J. Matrix Anal. Appl., 2007

One sketch for all: fast algorithms for compressed sensing.
Proceedings of the 39th Annual ACM Symposium on Theory of Computing, 2007

2006
Just relax: convex programming methods for identifying sparse signals in noise.
IEEE Trans. Inf. Theory, 2006

Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit.
Signal Process., 2006

Algorithms for simultaneous sparse approximation. Part II: Convex relaxation.
Signal Process., 2006

Algorithmic linear dimension reduction in the l_1 norm for sparse vectors
CoRR, 2006

Random Filters for Compressive Sampling and Reconstruction.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Row-Action Methods for Compressed Sensing.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Sparse Approximation Via Iterative Thresholding.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Random Filters for Compressive Sampling.
Proceedings of the 40th Annual Conference on Information Sciences and Systems, 2006

2005
Designing structured tight frames via an alternating projection method.
IEEE Trans. Inf. Theory, 2005

Recovery of short, complex linear combinations via 𝓁<sub>1</sub> minimization.
IEEE Trans. Inf. Theory, 2005

Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum.
SIAM J. Matrix Anal. Appl., 2005

Applications of sparse approximation in communications.
Proceedings of the 2005 IEEE International Symposium on Information Theory, 2005

Simultaneous sparse approximation via greedy pursuit.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Finite-Step Algorithms for Constructing Optimal CDMA Signature Sequences.
IEEE Trans. Inf. Theory, 2004

Greed is good: algorithmic results for sparse approximation.
IEEE Trans. Inf. Theory, 2004

Triangle Fixing Algorithms for the Metric Nearness Problem.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Improved sparse approximation over quasiincoherent dictionaries.
Proceedings of the 2003 International Conference on Image Processing, 2003


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