Fast Iterative Reconstruction of Band-Limited Images from Non-Uniform Sampling Values. - Hans Georg Feichtinger; Thomas Strohmer (CAIP, 1993)

How to recover smooth object boundaries in noisy medical images. - Thomas Strohmer; Thomas Binder; Michael Süssner (ICIP (1), 1996)

Computationally attractive reconstruction of bandlimited images from irregular samples. - Thomas Strohmer (IEEE Trans. Image Process., 1997)

On the estimation of the bandwidth of nonuniformly sampled signals. - Thomas Strohmer (ICASSP, 1999)

A Levinson-Galerkin Algorithm for Regularized Trigonometric Approximation. - Thomas Strohmer (SIAM J. Sci. Comput., 2000)

Numerical Harmonic Analysis and Image Processing. - Hans G. Feichtinger; Thomas Strohmer (Digital Image Analysis, 2001)

Optimal OFDM system design through optimal sphere coverings. - Thomas Strohmer; Scott Beaver (ICASSP, 2001)

Grassmannian signatures for CDMA systems. - Robert W. Heath Jr.; Thomas Strohmer; Arogyaswami Paulraj (GLOBECOM, 2003)

Optimal OFDM design for time-frequency dispersive channels. - Thomas Strohmer; Scott Beaver (IEEE Trans. Commun., 2003)

Grassmannian beamforming for multiple-input multiple-output wireless systems. - David James Love; Robert W. Heath Jr.; Thomas Strohmer (IEEE Trans. Inf. Theory, 2003)

Application of time-reversal with MMSE equalizer to UWB communications. - Thomas Strohmer; Majid Emami; Jan Hansen; George Papanicolaou; Arogyaswami Paulraj (GLOBECOM, 2004)

The finite section method and problems in frame theory. - Ole W. Christensen; Thomas Strohmer (J. Approx. Theory, 2005)

Wilson Bases for General Time-Frequency Lattices. - Gitta Kutyniok; Thomas Strohmer (SIAM J. Math. Anal., 2005)

Designing structured tight frames via an alternating projection method. - Joel A. Tropp; Inderjit S. Dhillon; Robert W. Heath Jr.; Thomas Strohmer (IEEE Trans. Inf. Theory, 2005)

A Randomized Solver for Linear Systems with Exponential Convergence. - Thomas Strohmer; Roman Vershynin (APPROX-RANDOM, 2006)

Frames and Overcomplete Representations in Signal Processing, Communications, and Information Theory. - Radu V. Balan; Yonina C. Eldar; Thomas Strohmer (EURASIP J. Adv. Signal Process., 2006)

Fast Reconstruction Methods for Bandlimited Functions from Periodic Nonuniform Sampling. - Thomas Strohmer; Jared Tanner (SIAM J. Numer. Anal., 2006)

On quasi-orthogonal signatures for CDMA systems. - Robert W. Heath Jr.; Thomas Strohmer; Arogyaswami Paulraj (IEEE Trans. Inf. Theory, 2006)

Fast Reconstruction Algorithms for Periodic Nonuniform Sampling with Applications to Time-Interleaved ADCs. - Thomas Strohmer; Jared Tanner (ICASSP (3), 2007)

Fast Algorithms for Blind Calibration in Time-Interleaved Analog-to-Digital Converters. - Thomas Strohmer; Jiadong Xu (ICASSP (3), 2007)

Compressed sensing radar. - Matthew A. Herman; Thomas Strohmer (ICASSP, 2008)

Constructing Packings in Grassmannian Manifolds via Alternating Projection. - Inderjit S. Dhillon; Robert W. Heath Jr.; Thomas Strohmer; Joel A. Tropp (Exp. Math., 2008)

Pulse Construction in OFDM Systems Via Convex Optimization. - Jiadong Xu; Thomas Strohmer (IEEE Trans. Commun., 2008)

Krylov Subspace Algorithms and Circulant-Embedding Method for Efficient Wideband Single-Carrier Equalization. - Raymond Guan; Thomas Strohmer (IEEE Trans. Signal Process., 2008)

High-resolution radar via compressed sensing. - Matthew A. Herman; Thomas Strohmer (IEEE Trans. Signal Process., 2009)

Compressive Spectral Clustering - Error Analysis. - Blake Hunter; Thomas Strohmer (AAAI Fall Symposium: Manifold Learning and Its Applications, 2010)

Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements - Blake Hunter; Thomas Strohmer (CoRR, 2010)

General Deviants: An Analysis of Perturbations in Compressed Sensing. - Matthew A. Herman; Thomas Strohmer (IEEE J. Sel. Top. Signal Process., 2010)

Compressed Remote Sensing of Sparse Objects. - Albert Fannjiang; Thomas Strohmer; Pengchong Yan (SIAM J. Imaging Sci., 2010)

Average power reduction for MSM optical signals via sparsity and uncertainty principle. - Jovana Ilic; Thomas Strohmer (IEEE Trans. Commun., 2010)

Some theoretical results for compressed MIMO radar. - Thomas Strohmer; Benjamin Friedlander (ACSCC, 2011)

Sparsity based adaptive thresholding for DFE in SC-FDMA. - Jovana Ilic; Thomas Strohmer (EUSIPCO, 2011)

PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming - Emmanuel J. Candès; Thomas Strohmer; Vladislav Voroninski (CoRR, 2011)

Eigenvalue Estimates and Mutual Information for the Linear Time-Varying Channel. - Brendan Farrell; Thomas Strohmer (IEEE Trans. Inf. Theory, 2011)

Analysis of Sparse MIMO Radar - Thomas Strohmer; Benjamin Friedlander (CoRR, 2012)

Remote sensing via ℓ1 minimization - Max Hügel; Holger Rauhut; Thomas Strohmer (CoRR, 2012)

Measure What Should be Measured: Progress and Challenges in Compressive Sensing - Thomas Strohmer (CoRR, 2012)

Map-invariant spectral analysis for the identification of DNA periodicities. - Ahmad A. Rushdi; Jamal Tuqan; Thomas Strohmer (EURASIP J. Bioinform. Syst. Biol., 2012)

Sparsity Enhanced Decision Feedback Equalization. - Jovana Ilic; Thomas Strohmer (IEEE Trans. Signal Process., 2012)

Accurate detection of moving targets via random sensor arrays and Kerdock codes - Thomas Strohmer; Haichao Wang (CoRR, 2013)

Bilinear compressed sensing for array self-calibration. - Benjamin Friedlander; Thomas Strohmer (ACSSC, 2014)

Remote Sensing via ℓ 1-Minimization. - Max Hügel; Holger Rauhut; Thomas Strohmer (Found. Comput. Math., 2014)

Foreword to the special section on compressive sensing applied to radar. - Matthias Weiss; Joachim H. G. Ender; Holger Rauhut; Gilda Schirinzi; Thomas Strohmer; Peter Willett 001 (IEEE Trans. Aerosp. Electron. Syst., 2014)

Sparse Signal Processing Concepts for Efficient 5G System Design. - Gerhard Wunder; Holger Boche; Thomas Strohmer; Peter Jung 001 (IEEE Access, 2015)

Self-Calibration and Biconvex Compressive Sensing. - Shuyang Ling; Thomas Strohmer (CoRR, 2015)

Localization of Matrix Factorizations. - Ilya A. Krishtal; Thomas Strohmer; Tim Wertz (Found. Comput. Math., 2015)

Phase Retrieval via Matrix Completion. - Emmanuel J. Candès; Yonina C. Eldar; Thomas Strohmer; Vladislav Voroninski (SIAM Rev., 2015)

Simultaneous blind deconvolution and blind demixing via convex programming. - Shuyang Ling; Thomas Strohmer (ACSSC, 2016)

Rapid, Robust, and Reliable Blind Deconvolution via Nonconvex Optimization. - Xiaodong Li; Shuyang Ling; Thomas Strohmer; Ke Wei (CoRR, 2016)

Self-Calibration via Linear Least Squares. - Shuyang Ling; Thomas Strohmer (CoRR, 2016)

Regularized Gradient Descent: A Nonconvex Recipe for Fast Joint Blind Deconvolution and Demixing. - Shuyang Ling; Thomas Strohmer (CoRR, 2017)

Painless Breakups - Efficient Demixing of Low Rank Matrices. - Thomas Strohmer; Ke Wei (CoRR, 2017)

Blind Deconvolution Meets Blind Demixing: Algorithms and Performance Bounds. - Shuyang Ling; Thomas Strohmer (IEEE Trans. Inf. Theory, 2017)

Self-Calibration and Bilinear Inverse Problems via Linear Least Squares. - Shuyang Ling; Thomas Strohmer (SIAM J. Imaging Sci., 2018)

What Happens on the Edge, Stays on the Edge: Toward Compressive Deep Learning. - Yang Li; Thomas Strohmer (CoRR, 2019)

The numerics of phase retrieval. - Albert Fannjiang; Thomas Strohmer (Acta Numer., 2020)

Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral Clustering. - Shuyang Ling; Thomas Strohmer (Found. Comput. Math., 2020)

When do birds of a feather flock together? k-Means, proximity, and conic programming. - Xiaodong Li; Yang Li; Shuyang Ling; Thomas Strohmer; Ke Wei (Math. Program., 2020)

Strong Consistency, Graph Laplacians, and the Stochastic Block Model. - Shaofeng Deng; Shuyang Ling; Thomas Strohmer (J. Mach. Learn. Res., 2021)

A Performance Guarantee for Spectral Clustering. - March Boedihardjo; Shaofeng Deng; Thomas Strohmer (SIAM J. Math. Data Sci., 2021)

GRAND++: Graph Neural Diffusion with A Source Term. - Matthew Thorpe; Tan Minh Nguyen; Hedi Xia; Thomas Strohmer; Andrea L. Bertozzi; Stanley J. Osher; Bao Wang 001 (ICLR, 2022)

Private measures, random walks, and synthetic data. - March Boedihardjo; Thomas Strohmer; Roman Vershynin (CoRR, 2022)

Semi-Supervised Clustering of Sparse Graphs: Crossing the Information-Theoretic Threshold. - Junda Sheng; Thomas Strohmer (CoRR, 2022)

Private Sampling: A Noiseless Approach for Generating Differentially Private Synthetic Data. - March Boedihardjo; Thomas Strohmer; Roman Vershynin (SIAM J. Math. Data Sci., 2022)

Covariance loss, Szemeredi regularity, and differential privacy. - March Boedihardjo; Thomas Strohmer; Roman Vershynin (CoRR, 2023)

Differentially private low-dimensional representation of high-dimensional data. - Yiyun He; Thomas Strohmer; Roman Vershynin; Yizhe Zhu (CoRR, 2023)

Fair Data Representation for Machine Learning at the Pareto Frontier. - Shizhou Xu; Thomas Strohmer (J. Mach. Learn. Res., 2023)

Privacy of Synthetic Data: A Statistical Framework. - March Boedihardjo; Thomas Strohmer; Roman Vershynin (IEEE Trans. Inf. Theory, 2023)

Monotone Operator Theory-Inspired Message Passing for Learning Long-Range Interaction on Graphs. - Justin M. Baker; Qingsong Wang; Martin Berzins; Thomas Strohmer; Bao Wang 001 (AISTATS, 2024)

On the (In)Compatibility between Group Fairness and Individual Fairness. - Shizhou Xu; Thomas Strohmer (CoRR, 2024)

Auto-Calibration and Biconvex Compressive Sensing with Applications to Parallel MRI. - Yuan Ni; Thomas Strohmer (CoRR, 2024)

An Algorithm for Streaming Differentially Private Data. - Girish Kumar; Thomas Strohmer; Roman Vershynin (CoRR, 2024)

Metric geometry of the privacy-utility tradeoff. - March Boedihardjo; Thomas Strohmer; Roman Vershynin (CoRR, 2024)

Convergence Analysis of the Alternating Anderson-Picard Method for Nonlinear Fixed-point Problems. - Xue Feng; M. Paul Laiu; Thomas Strohmer (CoRR, 2024)

Differentially Private Synthetic High-dimensional Tabular Stream. - Girish Kumar; Thomas Strohmer; Roman Vershynin (CoRR, 2024)

WHOMP: Optimizing Randomized Controlled Trials via Wasserstein Homogeneity. - Shizhou Xu; Thomas Strohmer (CoRR, 2024)

Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data. - March Boedihardjo; Thomas Strohmer; Roman Vershynin (Found. Comput. Math., 2024)

FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration. - Xue Feng; M. Paul Laiu; Thomas Strohmer (CPAL, 2025)

Machine Unlearning via Information Theoretic Regularization. - Shizhou Xu; Thomas Strohmer (CoRR, 2025)