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Thomas Strohmer
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- affiliation: University of California, Davis, USA
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2020 – today
- 2024
- [j37]March Boedihardjo
, Thomas Strohmer, Roman Vershynin:
Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data. Found. Comput. Math. 24(1): 179-226 (2024) - [c18]Justin M. Baker, Qingsong Wang, Martin Berzins, Thomas Strohmer, Bao Wang:
Monotone Operator Theory-Inspired Message Passing for Learning Long-Range Interaction on Graphs. AISTATS 2024: 2233-2241 - [i38]Shizhou Xu, Thomas Strohmer:
On the (In)Compatibility between Group Fairness and Individual Fairness. CoRR abs/2401.07174 (2024) - [i37]Yuan Ni, Thomas Strohmer:
Auto-Calibration and Biconvex Compressive Sensing with Applications to Parallel MRI. CoRR abs/2401.10400 (2024) - [i36]Girish Kumar, Thomas Strohmer, Roman Vershynin:
An Algorithm for Streaming Differentially Private Data. CoRR abs/2401.14577 (2024) - [i35]March Boedihardjo, Thomas Strohmer, Roman Vershynin:
Metric geometry of the privacy-utility tradeoff. CoRR abs/2405.00329 (2024) - [i34]Xue Feng, M. Paul Laiu, Thomas Strohmer:
Convergence Analysis of the Alternating Anderson-Picard Method for Nonlinear Fixed-point Problems. CoRR abs/2407.10472 (2024) - [i33]Girish Kumar, Thomas Strohmer, Roman Vershynin:
Differentially Private Synthetic High-dimensional Tabular Stream. CoRR abs/2409.00322 (2024) - [i32]Shizhou Xu, Thomas Strohmer:
WHOMP: Optimizing Randomized Controlled Trials via Wasserstein Homogeneity. CoRR abs/2409.18504 (2024) - 2023
- [j36]Shizhou Xu, Thomas Strohmer:
Fair Data Representation for Machine Learning at the Pareto Frontier. J. Mach. Learn. Res. 24: 331:1-331:63 (2023) - [j35]March Boedihardjo
Privacy of Synthetic Data: A Statistical Framework. IEEE Trans. Inf. Theory 69(1): 520-527 (2023) - [i31]March Boedihardjo, Thomas Strohmer, Roman Vershynin:
Covariance loss, Szemeredi regularity, and differential privacy. CoRR abs/2301.02705 (2023) - [i30]Yiyun He, Thomas Strohmer, Roman Vershynin, Yizhe Zhu:
Differentially private low-dimensional representation of high-dimensional data. CoRR abs/2305.17148 (2023) - 2022
- [j34]March Boedihardjo
Private Sampling: A Noiseless Approach for Generating Differentially Private Synthetic Data. SIAM J. Math. Data Sci. 4(3): 1082-1115 (2022) - [c17]Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang:
GRAND++: Graph Neural Diffusion with A Source Term. ICLR 2022 - [i29]Shizhou Xu, Thomas Strohmer:
Fair Data Representation for Machine Learning at the Pareto Frontier. CoRR abs/2201.00292 (2022) - [i28]March Boedihardjo
Private measures, random walks, and synthetic data. CoRR abs/2204.09167 (2022) - [i27]Junda Sheng, Thomas Strohmer:
Semi-Supervised Clustering of Sparse Graphs: Crossing the Information-Theoretic Threshold. CoRR abs/2205.11677 (2022) - 2021
- [j33]Shaofeng Deng, Shuyang Ling, Thomas Strohmer:
Strong Consistency, Graph Laplacians, and the Stochastic Block Model. J. Mach. Learn. Res. 22: 117:1-117:44 (2021) - [j32]March Boedihardjo
A Performance Guarantee for Spectral Clustering. SIAM J. Math. Data Sci. 3(1): 369-387 (2021) - [i26]March Boedihardjo, Thomas Strohmer, Roman Vershynin:
Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data. CoRR abs/2107.05824 (2021) - [i25]March Boedihardjo, Thomas Strohmer, Roman Vershynin:
Privacy of synthetic data: a statistical framework. CoRR abs/2109.01748 (2021) - [i24]March Boedihardjo, Thomas Strohmer, Roman Vershynin:
Private sampling: a noiseless approach for generating differentially private synthetic data. CoRR abs/2109.14839 (2021) - 2020
- [j31]Albert Fannjiang, Thomas Strohmer:
The numerics of phase retrieval. Acta Numer. 29: 125-228 (2020) - [j30]Shuyang Ling, Thomas Strohmer:
Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral Clustering. Found. Comput. Math. 20(3): 367-421 (2020) - [j29]Xiaodong Li, Yang Li, Shuyang Ling, Thomas Strohmer, Ke Wei:
When do birds of a feather flock together? k-Means, proximity, and conic programming. Math. Program. 179(1): 295-341 (2020) - [i23]Albert Fannjiang, Thomas Strohmer:
The Numerics of Phase Retrieval. CoRR abs/2004.05788 (2020) - [i22]Shaofeng Deng, Shuyang Ling, Thomas Strohmer:
Strong Consistency, Graph Laplacians, and the Stochastic Block Model. CoRR abs/2004.09780 (2020) - [i21]March Boedihardjo, Shaofeng Deng, Thomas Strohmer:
A Performance Guarantee for Spectral Clustering. CoRR abs/2007.05627 (2020)
2010 – 2019
- 2019
- [i20]Yang Li, Thomas Strohmer:
What Happens on the Edge, Stays on the Edge: Toward Compressive Deep Learning. CoRR abs/1909.01539 (2019) - 2018
- [j28]Shuyang Ling, Thomas Strohmer:
Self-Calibration and Bilinear Inverse Problems via Linear Least Squares. SIAM J. Imaging Sci. 11(1): 252-292 (2018) - [i19]Shuyang Ling, Thomas Strohmer:
Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral Clustering. CoRR abs/1806.11429 (2018) - 2017
- [j27]Shuyang Ling
Blind Deconvolution Meets Blind Demixing: Algorithms and Performance Bounds. IEEE Trans. Inf. Theory 63(7): 4497-4520 (2017) - [i18]Shuyang Ling, Thomas Strohmer:
Regularized Gradient Descent: A Nonconvex Recipe for Fast Joint Blind Deconvolution and Demixing. CoRR abs/1703.08642 (2017) - [i17]Thomas Strohmer, Ke Wei:
Painless Breakups - Efficient Demixing of Low Rank Matrices. CoRR abs/1703.09848 (2017) - 2016
- [c16]Shuyang Ling, Thomas Strohmer:
Simultaneous blind deconvolution and blind demixing via convex programming. ACSSC 2016: 1223-1227 - [i16]Xiaodong Li, Shuyang Ling, Thomas Strohmer, Ke Wei:
Rapid, Robust, and Reliable Blind Deconvolution via Nonconvex Optimization. CoRR abs/1606.04933 (2016) - [i15]Shuyang Ling, Thomas Strohmer:
Self-Calibration via Linear Least Squares. CoRR abs/1611.04196 (2016) - 2015
- [j26]Gerhard Wunder, Holger Boche, Thomas Strohmer, Peter Jung
Sparse Signal Processing Concepts for Efficient 5G System Design. IEEE Access 3: 195-208 (2015) - [j25]Ilya A. Krishtal
Localization of Matrix Factorizations. Found. Comput. Math. 15(4): 931-951 (2015) - [j24]Emmanuel J. Candès, Yonina C. Eldar, Thomas Strohmer, Vladislav Voroninski:
Phase Retrieval via Matrix Completion. SIAM Rev. 57(2): 225-251 (2015) - [i14]Shuyang Ling, Thomas Strohmer:
Self-Calibration and Biconvex Compressive Sensing. CoRR abs/1501.06864 (2015) - [i13]Shuyang Ling, Thomas Strohmer:
Blind Deconvolution Meets Blind Demixing: Algorithms and Performance Bounds. CoRR abs/1512.07730 (2015) - 2014
- [j23]Max Hügel, Holger Rauhut
Remote Sensing via ℓ 1-Minimization. Found. Comput. Math. 14(1): 115-150 (2014) - [j22]Matthias Weiss, Joachim H. G. Ender, Holger Rauhut
Foreword to the special section on compressive sensing applied to radar. IEEE Trans. Aerosp. Electron. Syst. 50(2): 807-808 (2014) - [c15]Benjamin Friedlander, Thomas Strohmer:
Bilinear compressed sensing for array self-calibration. ACSSC 2014: 363-367 - [i12]Gerhard Wunder, Holger Boche, Thomas Strohmer, Peter Jung
Sparse Signal Processing Concepts for Efficient 5G System Design. CoRR abs/1411.0435 (2014) - 2013
- [j21]Emmanuel J. Candès, Yonina C. Eldar, Thomas Strohmer, Vladislav Voroninski:
Phase Retrieval via Matrix Completion. SIAM J. Imaging Sci. 6(1): 199-225 (2013) - [i11]Thomas Strohmer, Haichao Wang:
Accurate detection of moving targets via random sensor arrays and Kerdock codes. CoRR abs/1301.3021 (2013) - 2012
- [j20]Ahmad A. Rushdi, Jamal Tuqan, Thomas Strohmer:
Map-invariant spectral analysis for the identification of DNA periodicities. EURASIP J. Bioinform. Syst. Biol. 2012: 16 (2012) - [j19]Jovana Ilic, Thomas Strohmer:
Sparsity Enhanced Decision Feedback Equalization. IEEE Trans. Signal Process. 60(5): 2422-2432 (2012) - [i10]Thomas Strohmer, Benjamin Friedlander:
Analysis of Sparse MIMO Radar. CoRR abs/1203.2690 (2012) - [i9]Max Hügel, Holger Rauhut, Thomas Strohmer:
Remote sensing via ℓ1 minimization. CoRR abs/1205.1366 (2012) - [i8]Thomas Strohmer:
Measure What Should be Measured: Progress and Challenges in Compressive Sensing. CoRR abs/1210.6730 (2012) - 2011
- [j18]Brendan Farrell, Thomas Strohmer:
Eigenvalue Estimates and Mutual Information for the Linear Time-Varying Channel. IEEE Trans. Inf. Theory 57(9): 5710-5719 (2011) - [c14]Thomas Strohmer, Benjamin Friedlander:
Some theoretical results for compressed MIMO radar. ACSCC 2011: 739-743 - [c13]Jovana Ilic, Thomas Strohmer:
Sparsity based adaptive thresholding for DFE in SC-FDMA. EUSIPCO 2011: 2210-2214 - [i7]Jovana Ilic, Thomas Strohmer:
Sparsity Enhanced Decision Feedback Equalization. CoRR abs/1103.5542 (2011) - [i6]Emmanuel J. Candès, Yonina C. Eldar, Thomas Strohmer, Vladislav Voroninski:
Phase Retrieval via Matrix Completion. CoRR abs/1109.0573 (2011) - [i5]Emmanuel J. Candès, Thomas Strohmer, Vladislav Voroninski:
PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming. CoRR abs/1109.4499 (2011) - 2010
- [j17]Matthew A. Herman, Thomas Strohmer:
General Deviants: An Analysis of Perturbations in Compressed Sensing. IEEE J. Sel. Top. Signal Process. 4(2): 342-349 (2010) - [j16]Albert Fannjiang, Thomas Strohmer, Pengchong Yan:
Compressed Remote Sensing of Sparse Objects. SIAM J. Imaging Sci. 3(3): 595-618 (2010) - [j15]Jovana Ilic, Thomas Strohmer:
Average power reduction for MSM optical signals via sparsity and uncertainty principle. IEEE Trans. Commun. 58(5): 1505-1513 (2010) - [c12]Blake Hunter, Thomas Strohmer:
Compressive Spectral Clustering - Error Analysis. AAAI Fall Symposium: Manifold Learning and Its Applications 2010 - [i4]Blake Hunter, Thomas Strohmer:
Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements. CoRR abs/1011.0997 (2010)
2000 – 2009
- 2009
- [j14]Matthew A. Herman, Thomas Strohmer:
High-resolution radar via compressed sensing. IEEE Trans. Signal Process. 57(6): 2275-2284 (2009) - [i3]Matthew A. Herman, Thomas Strohmer:
General Deviants: An Analysis of Perturbations in Compressed Sensing. CoRR abs/0907.2955 (2009) - 2008
- [j13]Inderjit S. Dhillon, Robert W. Heath Jr.
Constructing Packings in Grassmannian Manifolds via Alternating Projection. Exp. Math. 17(1): 9-35 (2008) - [j12]Jiadong Xu, Thomas Strohmer:
Pulse Construction in OFDM Systems Via Convex Optimization. IEEE Trans. Commun. 56(8): 1225-1230 (2008) - [j11]Raymond Guan, Thomas Strohmer:
Krylov Subspace Algorithms and Circulant-Embedding Method for Efficient Wideband Single-Carrier Equalization. IEEE Trans. Signal Process. 56(6): 2483-2495 (2008) - [c11]Matthew A. Herman, Thomas Strohmer:
Compressed sensing radar. ICASSP 2008: 1509-1512 - [i2]Brendan Farrell, Thomas Strohmer:
Eigenvalue Estimates and Mutual Information for the Linear Time-Varying Channel. CoRR abs/0802.4330 (2008) - [i1]Matthew A. Herman, Thomas Strohmer:
High-Resolution Radar via Compressed Sensing. CoRR abs/0803.2257 (2008) - 2007
- [c10]Thomas Strohmer, Jared Tanner:
Fast Reconstruction Algorithms for Periodic Nonuniform Sampling with Applications to Time-Interleaved ADCs. ICASSP (3) 2007: 881-884 - [c9]Thomas Strohmer, Jiadong Xu:
Fast Algorithms for Blind Calibration in Time-Interleaved Analog-to-Digital Converters. ICASSP (3) 2007: 1225-1228 - 2006
- [j10]Radu V. Balan, Yonina C. Eldar, Thomas Strohmer:
Frames and Overcomplete Representations in Signal Processing, Communications, and Information Theory. EURASIP J. Adv. Signal Process. 2006 (2006) - [j9]Thomas Strohmer, Jared Tanner:
Fast Reconstruction Methods for Bandlimited Functions from Periodic Nonuniform Sampling. SIAM J. Numer. Anal. 44(3): 1073-1094 (2006) - [j8]Robert W. Heath Jr.
On quasi-orthogonal signatures for CDMA systems. IEEE Trans. Inf. Theory 52(3): 1217-1226 (2006) - [c8]Thomas Strohmer, Roman Vershynin:
A Randomized Solver for Linear Systems with Exponential Convergence. APPROX-RANDOM 2006: 499-507 - 2005
- [j7]Ole W. Christensen
The finite section method and problems in frame theory. J. Approx. Theory 133(2): 221-237 (2005) - [j6]Gitta Kutyniok
Wilson Bases for General Time-Frequency Lattices. SIAM J. Math. Anal. 37(3): 685-711 (2005) - [j5]Joel A. Tropp
Designing structured tight frames via an alternating projection method. IEEE Trans. Inf. Theory 51(1): 188-209 (2005) - 2004
- [c7]Thomas Strohmer, Majid Emami, Jan Hansen
Application of time-reversal with MMSE equalizer to UWB communications. GLOBECOM 2004: 3123-3127 - 2003
- [j4]Thomas Strohmer, Scott Beaver:
Optimal OFDM design for time-frequency dispersive channels. IEEE Trans. Commun. 51(7): 1111-1122 (2003) - [j3]David James Love, Robert W. Heath Jr.
Grassmannian beamforming for multiple-input multiple-output wireless systems. IEEE Trans. Inf. Theory 49(10): 2735-2747 (2003) - [c6]Robert W. Heath Jr.
Grassmannian signatures for CDMA systems. GLOBECOM 2003: 1553-1557 - [c5]David J. Love, Robert W. Heath Jr.
Grassmannian beamforming for multiple-input multiple-output wireless systems. ICC 2003: 2618-2622 - 2001
- [c4]Thomas Strohmer, Scott Beaver:
Optimal OFDM system design through optimal sphere coverings. ICASSP 2001: 2373-2376 - [p1]Hans G. Feichtinger, Thomas Strohmer:
Numerical Harmonic Analysis and Image Processing. Digital Image Analysis 2001: 7-47 - 2000
- [j2]Thomas Strohmer:
A Levinson-Galerkin Algorithm for Regularized Trigonometric Approximation. SIAM J. Sci. Comput. 22(4): 1160-1183 (2000)
1990 – 1999
- 1999
- [c3]Thomas Strohmer:
On the estimation of the bandwidth of nonuniformly sampled signals. ICASSP 1999: 2047-2050 - 1997
- [j1]Thomas Strohmer:
Computationally attractive reconstruction of bandlimited images from irregular samples. IEEE Trans. Image Process. 6(4): 540-548 (1997) - 1996
- [c2]Thomas Strohmer, Thomas Binder, Michael Süssner:
How to recover smooth object boundaries in noisy medical images. ICIP (1) 1996: 331-334 - 1993
- [c1]Hans Georg Feichtinger, Thomas Strohmer:
Fast Iterative Reconstruction of Band-Limited Images from Non-Uniform Sampling Values. CAIP 1993: 82-89
Coauthor Index
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last updated on 2024-10-22 20:16 CEST by the dblp team
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