Papers

repositories

• List of publications — April 2025
• Bibtex bibliography — April 2025
• Google Scholar page
• CaltechAUTHORS
• arXiv

in the pipeline...

• Successive randomized compression: A randomized algorithm for the compressed MPO-MPS product
  C. Camaño, E. N. Epperly, and J. A. Tropp Apr. 2025
  • arXiv
• Comparison theorems for the minimum eigenvalue of a random positive-semidefinite matrix
  J. A. Tropp Jan. 2025
  • arXiv
• Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky
  E. N. Epperly, J. A. Tropp, and R. J. Webber Oct. 2024
  • arXiv
• A new approach to strong convergence
  C.-F. Chen, J. Garza-Vargas, J. A. Tropp, and R. van Handel Ann. Math. Accepted, Feb. 2025
  • arXiv
• Randomized matrix computations: Themes and variations
  A. Kireeva and J. A. Tropp Caltech CMS Lecture Notes 2023-02 July 2023. To appear in CIME Lecture Notes series
  • Notes
  • arXiv
  • doi
• Randomized algorithms for low-rank matrix approximation: Design, analysis, and applications
  J. A. Tropp and R. J. Webber Aug. 2023
  • arXiv
• Robust, randomized preconditioning for kernel ridge regression
  M. Díaz, E. N. Epperly, Z. Frangella, J. A. Tropp, and R. J. Webber Apr. 2023
  • arXiv
• Sharp phase transitions in Euclidean integral geometry
  M. Lotz and J. A. Tropp High-Dimensional Probability X Accepted, Apr. 2025
  • Report
  • arXiv
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• Binary component decomposition. Part II: The asymmetric case
  R. Kueng and J. A. Tropp July 2019
  • arXiv

Books

• An introduction to matrix concentration inequalities
  J. A. Tropp Foundations & Trends in Machine Learning Vol. 8, num. 1–2, pp. 1–230, 2015
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Lecture notes

• CMS/ACM 117: Probability Theory & Computational Mathematics
  J. A. Tropp Caltech CMS Lecture Notes 2023-01
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• ACM 204: Matrix Analysis
  J. A. Tropp Caltech CMS Lecture Notes 2022-01
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• ACM 217: Probability in High Dimensions
  J. A. Tropp Caltech CMS Lecture Notes 2021-01 Corrected, March 2023
  • Notes
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• ACM 204: Randomized Algorithms for Matrix Computations
  J. A. Tropp Caltech CMS Lecture Notes 2020-01
  • Notes
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• Matrix Concentration & Computational Linear Algebra
  J. A. Tropp Caltech CMS Lecture Notes 2019-01 ENS Short Course, Paris, July 2019
  • Notes
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• ACM 204: Lectures on Convex Geometry
  J. A. Tropp Caltech CMS Lecture Notes 2018-01
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Book chapters

• Randomized numerical linear algebra: Foundations and algorithms
  P.-G. Martinsson and J. A. Tropp Acta Numerica Vol. 29, pp. 403–572, Cambridge Univ. Press, 2020
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  • arXiv
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• Concentration of the intrinsic volumes of a convex body
  M. Lotz, M. B. McCoy, I. Nourdin, G. Peccati, and J. A. Tropp Geometric Aspects of Functional Analysis (GAFA), Israel Seminar 2017–2019, Vol. II Lecture Notes in Mathematics, Vol. 2255, pp. 139–167, Springer, 2020
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  • arXiv
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• The expected norm of a sum of independent random matrices: An elementary approach
  J. A. Tropp High-Dimensional Probability VII: The Cargèse Volume Progress in Probability, Vol. 71, pp. 173–202, Birkhäuser, 2016
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  • arXiv
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• Convex recovery of a structured signal from independent random linear measurements
  J. A. Tropp Sampling Theory, a Renaissance pp. 67–101, Birkhäuser, 2015
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  • arXiv
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Book reviews

• “A mathematical introduction to compressive sampling” by Simon Foucart and Holger Rauhut
  J. A. Tropp Bull. Amer. Math. Soc. Vol. 54, num. 1, pp. 151–165, 2017
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Theses

• Topics in Sparse Approximation
  J. A. Tropp PhD dissertation, UT-Austin, 2004
  • Thesis
• Infinitesimals: History and Application
  J. A. Tropp Senior thesis, UT-Austin, 1999
  • Thesis

Dissertations Supervised

• Recovering Structured Low-rank Operators Using Nuclear Norms
  J. J. Bruer PhD dissertation, Caltech, 2017
  • Thesis
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• Concentration Inequalities of Random Matrices and Solving Ptychography with a Convex Relaxation
  Y. R. Chen PhD dissertation, Caltech, 2017
  • Thesis
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• A Geometric Analysis of Convex Demixing
  M. B. McCoy PhD dissertation, Caltech, 2013
  • Thesis
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• Topics in Randomized Numerical Linear Algebra
  A. Gittens PhD dissertation, Caltech, 2013
  • Thesis
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• Convex Analysis for Minimizing and Learning Submodular functions
  P. Stobbe PhD dissertation, Caltech, 2013
  • Thesis
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Journals, conferences, and tech reports

2025 ⬆

• Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations
  Y. Chen, E. N. Epperly, J. A. Tropp, and R. J. Webber Comm. Pure Appl. Math. Vol. 78, num. 5, pp. 995-1041, May 2025
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  • arXiv
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2024 ⬆

• Fast & accurate randomized algorithms for linear systems and eigenvalue problems
  Y. Nakatsukasa and J. A. Tropp SIAM J. Matrix Anal. Appl. Vol. 45, num. 2, pp. 1183-1214, 2024
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  • arXiv
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• Sparse random Hamiltonians are quantumly easy
  C.-F. Chen, A. M. Dalzell, M. Berta, F. G. S. L. Brandão, and J. A. Tropp Phys. Rev. X: Quantum Vol. 14, num. 1, page 011014, Feb. 2024. Short plenary talk at QIP 2023, Feb. 2023 QIP 2023, Best Student Paper Prize
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  • arXiv
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• XTrace: Making the most of every sample in stochastic trace estimation
  E. N. Epperly, J. A. Tropp, and R. J. Webber SIAM J. Matrix Anal. Appl. Vol. 45, num. 1, pp. 1-23, 2024
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  • arXiv
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• Efficient error and variance estimation for randomized matrix computations
  E. N. Epperly and J. A. Tropp SIAM J. Sci. Comput. Vol. 46, num. 1, pp. A508-528, 2024
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  • arXiv
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2023 ⬆

• Randomized Nyström preconditioning
  Z. Frangella, J. A. Tropp, and M. Udell SIAM J. Matrix Anal. Appl. Vol. 44, num. 2, pp. 718–752, 2023
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  • arXiv
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2022 ⬆

• Learning to forecast dynamical systems from streaming data
  D. Giannakis, A. Henriksen, J. A. Tropp, and R. Ward SIAM J. Applied Dynamical Sys. Vol. 22, num. 2, pp. 527–558, 2022
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  • arXiv
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• Matrix concentration for products
  D. Huang, J. Niles-Weed, J. A. Tropp, and R. Ward Found. Comput. Math. Vol. 22, pp. 1767–1799, 2022
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  • arXiv
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• Randomized block Krylov methods for approximating extreme eigenvalues
  J. A. Tropp Num. Math. Vol. 150, pp. 217–255, 2022
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  • arXiv
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2021 ⬆

• Inference of black hole fluid dynamics from sparse interferometric measurements
  A. Levis, D. Lee, J. A. Tropp, C. F. Gammie, and K. L. Bouman Proc. IEEE Conf. Computer Vision (ICCV 2021) pp. 2340–2349, 2021
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  • Web
  • github
  • ICCV
• An optimal-storage approach to semidefinite programming using approximate complementarity
  L. Ding, A. Yurtsever, V. Cevher, J. A. Tropp, and M. Udell SIAM J. Optim. Vol. 31, num. 4, pp. 2695–2725, 2021 INFORMS Optimization Society Student Paper Prize, 2019
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  • arXiv
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• Concentation for random product formulas
  C.-F. Chen, H.-Y. Huang, R. Kueng, and J. A. Tropp Phys. Rev. X: Quantum Vol. 2, num. 040305, Oct. 2021 Oral presentation, TQC 2021
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  • arXiv
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• From Poincaré inequalities to nonlinear matrix concentration
  D. Huang and J. A. Tropp Bernoulli Vol. 27, num. 3, pp. 1724–1744, Aug. 2021
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  • arXiv
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• Nonlinear matrix concentration via semigroup methods
  D. Huang and J. A. Tropp Electron. J. Probability Vol. 26, article no. 8, pp. 1–31, 2021
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  • arXiv
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• Binary component decomposition. Part I: The positive-semidefinite case
  R. Kueng and J. A. Tropp SIAM J. Math. Data Sci. Vol. 3, num. 2, pp. 544–572, 2021
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  • arXiv
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• Scalable semidefinite programming
  A. Yurtsever, J. A. Tropp, O. Fercoq, M. Udell, and V. Cevher SIAM J. Math. Data Sci. Vol. 3, num. 1, pp. 171–200, 2021
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  • arXiv
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2020 ⬆

• Low-rank Tucker approximation of a tensor from streaming data
  Y. Sun, Y. Guo, J. A. Tropp, and M. Udell SIAM J. Math. Data Sci. Vol. 2, num. 4, pp. 1123–1150, 2020
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  • arXiv
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• Fast state tomography with optimal error bounds
  M. Guţă, J. Kahn, R. Kueng, and J. A. Tropp J. Phys. A: Math. Theor. Vol. 53, article 204001, 2020
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  • arXiv
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2019 ⬆

• Streaming low-rank matrix approximation with an application to scientific simulation
  J. A. Tropp, A. Yurtsever, M. Udell, and V. Cevher SIAM J. Sci. Comp. Vol. 41, num. 4, pp. A2430–A2463, 2019
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  • arXiv
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2018 ⬆

• Tensor random projection for low-memory dimension reduction
  Y. Sun, Y. Guo, J. A. Tropp, and M. Udell NeurIPS Workshop on Relational Representation Learning, 2018
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  • arXiv
  • NeurIPS
• Simplicial faces of the set of correlation matrices
  J. A. Tropp Discrete Comput. Geom. Vol. 60, num. 2, pp. 512–529, 2018
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  • arXiv
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• Universality laws for randomized dimension reduction, with applications
  S. Oymak and J. A. Tropp Inform. Inference Vol. 7, num. 3, pp. 337–446, 2018
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  • arXiv
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• Second-order matrix concentration inequalities
  J. A. Tropp Appl. Comput. Harmon. Anal. Vol. 44, num. 3, pp. 700–736, 2018
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  • arXiv
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• Analysis of randomized block Krylov methods
  J. A. Tropp Caltech ACM Report 2018-02, 2018
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2017 ⬆

• Fixed-rank approximation of a positive-semidefinite matrix from streaming data
  J. A. Tropp, A. Yurtsever, M. Udell, and V. Cevher Adv. Neural Information Processing Systems (NeurIPS) Vol. 30, 2017
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  • arXiv
  • NeurIPS
• Sketchy decisions: Convex low-rank matrix optimization with optimal storage
  A. Yurtsever, M. Udell, J. A. Tropp, and V. Cevher Proc. 20th Ann. Conf. Artificial Intelligence and Statistics (AISTATS) 2017 Oral presentation, top 5% of submissions
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  • arXiv
  • AISTATS
• Practical sketching algorithms for low-rank matrix approximation
  J. A. Tropp, A. Yurtsever, M. Udell, and V. Cevher SIAM J. Matrix Anal. Appl. Vol. 38, num. 4, pp. 1454–1485, 2017
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  • arXiv
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• The achievable performance of convex demixing
  M. B. McCoy and J. A. Tropp Caltech ACM Report 2017-02, 2017
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  • arXiv
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2016 ⬆

• Efron–Stein inequalities for random matrices
  D. Paulin, L. Mackey, and J. A. Tropp Ann. Probab. Vol. 44, num. 5, pp. 3431–3473, 2016
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  • arXiv
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2015 ⬆

• Integer factorization of a positive-definite matrix
  J. A. Tropp SIAM J. Discrete Math. Vol. 29, num. 4, pp. 1783–1791, 2015
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  • arXiv
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• Designing statistical estimators that balance sample size, risk, and computational cost
  J. J. Bruer, J. A. Tropp, V. Cevher, and S. J. Becker IEEE J. Selected Topics Signal Processing Vol. 9, num. 4, pp. 612–624, 2015
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• Solving ptychography with a convex relaxation
  R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang New J. Phys. Vol. 17, article 053044, 2015
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  • arXiv
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• Robust computation of linear models by convex relaxation
  G. Lerman, M. B. McCoy, J. A. Tropp, and T. Zhang Found. Comput. Math. Vol. 15, num. 2, pp. 363–410, 2015
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  • arXiv
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2014 ⬆

• Time–data tradeoffs by aggressive smoothing
  J. J. Bruer, J. A. Tropp, V. Cevher, and S. J. Becker Adv. Neural Information Processing Systems (NeurIPS) Vol. 27, 2014
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  • NeurIPS
• Living on the edge: Phase transitions in convex programs with random data
  D. Amelunxen, M. Lotz, M. B. McCoy, and J. A. Tropp Inform. Inference Vol. 3, num. 3, pp. 224–294, 2014 Inaugural IMA Information & Inference Best Paper Award, 2015
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• A low-order decomposition of turbulent channel flow via resolvent analysis and convex optimization
  R. Moarref, M. R. Jovanović, J. A. Tropp, A. S. Sharma, and B. J. McKeon Phys. Fluids Vol. 26, article 051701, 2014
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  • arXiv
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• Sharp recovery bounds for convex demixing, with applications
  M. B. McCoy and J. A. Tropp Found. Comput. Math. Vol. 14, num. 3, pp. 503–567, 2014
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  • arXiv
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• From Steiner formulas for cones to concentration of intrinsic volumes
  M. B. McCoy and J. A. Tropp Discrete Comput. Geom. Vol. 51, num. 4, 926–963, 2014
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  • arXiv
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• Matrix concentration inequalities via the method of exchangeable pairs
  L. Mackey, M. B. Jordan, R. Y. Chen, B. Farrell, and J. A. Tropp Ann. Probab. Vol. 42, num. 3, pp. 906–945, 2014
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  • arXiv
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• Subadditivity of matrix φ-entropy and concentration of random matrices
  R. Y. Chen and J. A. Tropp Electron. J. Probab. Vol. 19, article 27, pp. 1–30, 2014
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  • arXiv
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• Compact representation of wall-bounded turbulence using compressive sampling
  J.-L. Bourguignon, J. A. Tropp, A. S. Sharma, and B. J. McKeon Phys. Fluids Vol. 26, article 015109, 2014
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• Paved with good intentions: Analysis of a randomized block Kaczmarz method
  D. Needell and J. A. Tropp Linear Algebra Appl. Vol. 441, pp. 199–221, 2014
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  • arXiv
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• Tail bounds for all eigenvalues of a sum of random matrices
  A. Gittens and J. A. Tropp Caltech ACM Report 2014-02, 2014
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  • arXiv
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• Error bounds for random matrix approximation schemes
  A. Gittens and J. A. Tropp Caltech ACM Report 2014-01, 2014
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  • arXiv
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• A foundation for analytical developments in the logarithmic region of turbulent channels
  R. Moarref, A. S. Sharma, J. A. Tropp, and B. J. McKeon Available from arXiv, 2014
  • arXiv

2013 ⬆

• Model-based scaling of the streamwise energy density in high-Reynolds-number turbulent channels
  R. Moarref, A. S. Sharma, J. A. Tropp, and B. J. McKeon J. Fluid Mech. Vol. 734, pp. 275–316, 2013
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• Restricted isometries for partial random circulant matrices
  G. Pfander, H. Rauhut, and J. A. Tropp Probab. Theory Related Fields Vol. 156, num. 3–4, pp. 707–737, 2013
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2012 ⬆

• Factoring nonnegative matrices with linear programs
  V. Bittorf, B. Recht, C. Ré, and J. A. Tropp Adv. Neural Information Processing Systems (NeurIPS) Vol. 25, pp. 1223–1231, 2012
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  • arXiv
  • NeurIPS
• The masked sample covariance estimator: An analysis via matrix concentration inequalities
  R. Y. Chen, A. Gittens, and J. A. Tropp Inform. Inference Vol. 1, num. 1, pp. 2–20, 2012
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• Restricted isometries for partial random circulant matrices
  H. Rauhut, J. Romberg, and J. A. Tropp Appl. Comput. Harmon. Anal. Vol. 32, num. 2, pp. 242–254, 2012
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  • arXiv
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• User-friendly tail bounds for sums of random matrices
  J. A. Tropp Found. Comput. Math. Vol. 12, num. 4, pp. 389–434, 2012
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  • arXiv
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• A comparison principle for functions of a uniformly random subspace
  J. A. Tropp Probab. Theory Related Fields Vol. 153, num. 3–4, pp. 759–769, 2012
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  • arXiv
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• From joint convexity of quantum relative entropy to a concavity theorem of Lieb
  J. A. Tropp Proc. Amer. Math. Soc. Vol. 140, num. 5, pp. 1757–1760, 2012
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2011 ⬆

• Two proposals for robust PCA using semidefinite prorgamming
  M. B. McCoy and J. A. Tropp Electron. J. Stat. Vol. 5, pp. 1123–1160, 2011
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• Improved analysis of the subsampled randomized Hadamard transform
  J. A. Tropp Adv. Adapt. Data Anal. Vol. 3, num. 1–2, pp. 115—126, 2011
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  • arXiv
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• Freedman's inequality for matrix martingales
  J. A. Tropp Electron. J. Probab. Vol. 16, pp. 262—270, 2011
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• Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
  N. Halko, P.-G. Martinsson, and J. A. Tropp SIAM Rev. Vol. 53, num. 2, pp. 217—288, 2011
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  • arXiv
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• Large-scale PCA with sparsity constraints
  C. Probel and J. A. Tropp Caltech ACM Report 2011-02, 2011
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2010 ⬆

• Practical large-scale optimization for max-norm regularization
  J. Lee, B. Recht, R. Salkhutdinov, N. Srebro, and J. A. Tropp Adv. Neural Information Processing Systems (NeurIPS) Vol. 23, pp. 1297–1305, 2010
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  • NeurIPS
• The sparsity gap: Uncertainty principles proportional to dimension
  J. A. Tropp Proc. 44th Ann. Conf. Information Sciences and Systems (CISS) 2010
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• Computational methods for sparse solution of linear inverse methods
  J. A. Tropp and S. J. Wright Proc. IEEE Vol. 98, num. 5, pp. 948–958, 2010
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• Beyond Nyquist: Efficient sampling of sparse, bandlimited signals
  J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk IEEE Trans. Inform. Theory Vol. 56, num. 1, pp. 520—544, 2010
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  • arXiv
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2009 ⬆

• Column subset selection, matrix factorization, and eigenvalue optimization
  J. A. Tropp Proc. 2009 ACM–SIAM Symp. Discrete Algorithms pp. 978–986, 2009
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  • arXiv
  • SODA
• CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
  D. Needell and J. A. Tropp Appl. Comput. Harmon. Anal. Vol. 26, pp. 301–321, 2009 Selected as the ScienceWatch fast-breaking paper in mathematics, Aug. 2010 Selected for “Research Highlights” section of Communications of the ACM, Dec. 2010
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  • CACM
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2008 ⬆

• Efficient sampling of sparse wideband analog signals
  M. Mishali, Y. C. Eldar, and J. A. Tropp 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel pp. 290–294 Best student paper award
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• Greedy signal recovery review
  D. Needell, J. A. Tropp, and R. Vershynin Proc. 42nd Asilomar Conf. Signals, Systems and Computers pp. 1048–1050, 2008
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• Norms of random submatrices and sparse approximation
  J. A. Tropp Comptes Rendus Acad. Sci. Paris, Ser. I Vol. 346, num. 23–24, pp. 1271–1274, 2008
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• On the linear independence of spikes and sines
  J. A. Tropp J. Fourier Anal. Appl. Vol. 14, num. 5–6, pp. 838—858, 2008
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• The metric nearness problem
  J. Brickell, I. S. Dhillon, S. Sra, and J. A. Tropp SIAM J. Matrix Anal. Appl. Vol. 30, num. 1, pp. 375–396, 2008 SIAM Outstanding Paper Prize, 2011
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• A tutorial on fast Fourier sampling
  A. C. Gilbert, M. J. Strauss, and J. A. Tropp IEEE Signal Processing Mag. Vol. 25, num. 2, pp. 57–66, 2008
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• Constructing packings in Grassmannian manifolds via alternating projection
  I. S. Dhillon, R. W. Heath Jr., T. Strohmer, and J. A. Tropp Exper. Math. Vol. 17, num. 1, pp. 9–35, 2008
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• On the conditioning of random subdictionaries
  J. A. Tropp Appl. Comput. Harmon. Anal. Vol. 25, num. 1, pp. 1–24, 2008 Eighth Monroe H. Martin Prize, 2011
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• On the random paving property for uniformly bounded matrices
  J. A. Tropp Studia Math. Vol. 185, num. 1, pp. 67–82, 2008
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2007 ⬆

• One sketch for all: Fast algorithms for compressed sensing
  A. C. Gilbert, M. J. Strauss, J. A. Tropp, and R. Vershynin Proc. 39th Ann. ACM Symp. Theory of Computing (STOC07) pp. 237--246, 2007
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• Signal recovery from random measurements via Orthogonal Matching Pursuit
  J. A. Tropp and A. C. Gilbert IEEE Trans. Inform. Theory Vol. 53, num. 12, pp. 4655–4666, 2007
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• Matrix nearness problems with Bregman divergences
  I. S. Dhillon and J. A. Tropp SIAM J. Matrix Anal. Appl. Vol. 29, num. 4, pp. 1120–1146, 2007
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• On the existence of equiangular tight frames
  M. Sustik, J. A. Tropp, I. S. Dhillon, and R. W. Heath Jr. Linear Algebra Appl. Vol. 426, num. 2–3, pp. 619–635, 2007
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2006 ⬆

• Algorithmic linear dimension reduction in the ℓ₁ norm for sparse vectors
  A. C. Gilbert, M. J. Strauss, J. A. Tropp, and R. Vershynin Proc. 44th Ann. Allerton Conf. Communication, Control, and Computing pp. 1411–1418, 2006
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  • arXiv
  • Allerton
• Sparse approximation via iterative thresholding
  K. K. Herrity, A. C. Gilbert, and J. A. Tropp Proc. 2006 IEEE Intl. Conf. Acoustics Speech and Signal Processing (ICASSP) Vol. III, pp. 624–627, 2006
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• Row-action methods for compressed sensing
  S. Sra and J. A. Tropp Proc. 2006 IEEE Intl. Conf. Acoustics Speech and Signal Processing (ICASSP) Vol. III, pp. 868–871, 2006
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• Random filters for compressive sampling and reconstruction
  J. A. Tropp, M. B. Wakin, M. F. Duarte, D. Baron, and R. G. Baraniuk Proc. 2006 IEEE Intl. Conf. Acoustics Speech and Signal Processing (ICASSP) Vol. III, pp. 872–875, 2006
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• Sublinear approximation of signals
  A. C. Gilbert, M. J. Strauss, J. A. Tropp, and R. Vershynin Proc. SPIE 6232, Intelligent Integrated Microsystems 2006
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• Random filters for compressive sampling
  J. A. Tropp Proc. 40th Ann. Conf. Information Sciences and Systems (CISS) 2006
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• Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit
  J. A. Tropp, A. C. Gilbert, and M. J. Strauss Signal Processing Vol. 86, num. 3, pp. 572–588, 2006 EURASIP Best Paper Award in Signal Processing, 2009
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• Algorithms for simultaneous sparse approximation. Part II: Convex relaxation
  J. A. Tropp Signal Processing Vol. 86, num. 3, pp. 589–602, 2006
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• Just relax: Convex programming methods for identifying sparse signals
  J. A. Tropp IEEE Trans. Inform. Theory Vol. 52, num. 3, pp. 1030–1051, 2006
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  • Corrig.
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2005 ⬆

• Applications of sparse approximation in communications
  A. C. Gilbert and J. A. Tropp Proc. 2005 IEEE Intl. Symp. Information Theory (ISIT) pp. 1000–1004, 2005
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• Simultaneous sparse approximation via greedy pursuit
  J. A. Tropp, A. C. Gilbert, and M. J. Strauss Proc. 2005 IEEE Intl. Conf. Acoustics Speech and Signal Processing (ICASSP) Vol. V, pp. 721–724, 2005
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• Average-case analysis of greedy pursuit
  J. A. Tropp Proc. SPIE 5914, Wavelets XI paper 591412, 2005
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• Complex equiangular tight frames
  J. A. Tropp Proc. SPIE 5914, Wavelets XI paper 591401, 2005
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• Generalized finite algorithms for constructing Hermitian matrices with prescribed diagonal and spectrum
  I. S. Dhillon, R. W. Heath Jr., M. Sustik, and J. A. Tropp SIAM J. Matrix Anal. Appl. Vol. 27, num. 1, pp. 61–71, 2005
  • Paper
  • doi
• Recovery of short complex linear combinations via ℓ₁-minimization
  J. A. Tropp IEEE Trans. Inform. Theory Vol. 51, num. 4, pp. 1568–1570, 2005
  • Preprint
  • doi
• Designing structured tight frames via alternating projection
  J. A. Tropp, I. S. Dhillon, R. W. Heath Jr., and T. Strohmer IEEE Trans. Inform. Theory Vol. 51, num. 1, pp. 188–209, 2005
  • Preprint
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2004 ⬆

• Triangle fixing algorithms for the metric nearness problem
  I. S. Dhillon, S. Sra, and J. A. Tropp Adv. Neural Information Processing Systems (NeurIPS) Vol. 17, 2004
  • Paper
  • NeurIPS
• Construction of equiangular signatures for synchronous CDMA systems
  R. W. Heath Jr., J. A. Tropp, I. S. Dhillon, and T. Strohmer Proc. 8th IEEE Symp. Spread Spectrum Techniques and Applications (ISSSTA) pp. 708–712, 2004
  • Preprint
  • doi
• Optimal CDMA signatures: A finite-step approach
  J. A. Tropp, I. S. Dhillon, and R. W. Heath Jr. Proc. 8th IEEE Symp. Spread Spectrum Techniques and Applications (ISSSTA) pp. 335–340, 2004
  • Paper
  • doi
• Finite-step algorithms for constructing optimal CDMA signature sequences
  J. A. Tropp, I. S. Dhillon, and R. W. Heath Jr. IEEE Trans. Inform. Theory Vol. 50, num. 11, pp. 2916–2921, 2004
  • Preprint
  • doi
• Greed is good: Algorithmic results for sparse approximation
  J. A. Tropp IEEE Trans. Inform. Theory Vol. 50, num. 10, pp. 188–209, 2004
  • Preprint
  • doi

2003 ⬆

• CDMA signature sequences with low peak-to-average-power ratio via alternating projection
  J. A. Tropp, I. S. Dhillon, R. W. Heath Jr., and T. Strohmer Proc. 37th Asilomar Conf. Signals, Systems, and Computers Vol. 1, pp. 475–479, 2003
  • Preprint
  • doi
• Improved sparse approximation of quasiincoherent dictionaries
  J. A. Tropp, A. C. Gilbert, S. Muthukrishnan, and M. J. Strauss Proc. 2003 IEEE Intl. Conf. Image Processing (ICIP) Vol. 1, pp. 37–40, 2003
  • Preprint
  • doi
• Optimal CDMA signature sequences, inverse eigenvalue problems, and alternating minimization
  J. A. Tropp, R. W. Heath Jr., and T. Strohmer Proc. IEEE Intl. Symp. Information Theory p. 407, 2003
  • Preprint
  • doi