Overview

Sparse recovery asks how to identify a small set of nonzero coefficients and estimate their values from incomplete or noisy observations, a problem central to compressed sensing, imaging, and high-dimensional regression. Common approaches include convex ℓ1 regularization, greedy and hard-thresholding algorithms, Bayesian and nonconvex penalties, and learned or unrolled methods that incorporate structure such as groups, blocks, or dictionaries. Theory uses tools such as restricted isometry, mutual coherence, and geometric complexity to establish recovery conditions, while newer work extends guarantees to online, nonlinear, and adversarially corrupted settings. A continuing challenge is balancing statistical accuracy and robustness against computational cost, especially when measurements are highly correlated or the assumed sparse representation is imperfect.

Latest papers

CardsList

77 papers11 papers in the last four weeks, up 38% on the four weeks before. 0.1% of all new papers.

  1. Threshold Compatibility and Support-Selection Diagnostics in Neural Discovery of Partial Differential Equations

    Oct 27, 2026Zeen SongPDE DiscoveryModel Selection

  2. A knowledge-driven nonconvex square-root regularization framework for joint group sparsity and structured smoothness

    Oct 26, 2026Wanling Xie, Hu YangStructured SparsitySparse Recovery

  3. Sparse Reconstruction by Direct Measurement-to-Field Generation in Function Space

    Oct 26, 2026Linzheng Wang, Jason Chen, Nicolas Tricard +3Sparse RecoveryInverse Problems

  4. Distinguishability and Recovery for a Doubly Sparse Spiked Wigner Model

    Oct 16, 2026Ioana Dumitriu, JD Flynn, Zhichao WangSparse RecoveryRandom Matrix Theory

  5. LGGS: Longitudinal MRI Reconstruction via Guided Group Sparsity

    Oct 15, 2026Nikola Janjušević, Hersh Chandarana, Yao Wang +1Accelerated MRI ReconstructionLongitudinal Medical Image Analysis

  6. Multiscale Generalized Sparse Plane Wave Decomposition in the Spherical Harmonic Domain

    Oct 15, 2026Huseyin HacihabibogluSpatial AudioSparse Recovery

  7. Readout Scaling Shapes Sparse Feature Recovery

    Oct 13, 2026Brian Xiao, Sarah WilsonSparse AutoencodersSparse Recovery

  8. Learning Incompressible 3D Flows from Sparse Samples: A Set Transformer Approach to Divergence-Free Kernel Fitting

    Oct 12, 2026Ramzi Idoughi, Radouan Boukharfane, Peter WonkaSet TransformerComputational Fluid Dynamics

  9. A Physics-Informed Hybrid Forward-Inverse Machine Learning Framework for High-Dimensional Sparse Recipe Reconstruction

    Oct 8, 2026Md. Muqtadir Fuad, Md. Istiak Adnan, Ridwan Al AzizInverse DesignSparse Recovery

  10. Robust Tensor Completion via Reflective Convolution Nuclear Norm Minimization

    Oct 4, 2026Weiguo Zhou, Feng Zhang, Wenjin Qin +1Tensor CompletionNuclear Norm Minimization

  11. Non-Adaptive Learning of Sparse Erdős--Rényi Graphs via Affine Splitting

    Sep 27, 2026Hoang TaGraph Structure LearningSparse Recovery

  12. Efficient Support Recovery of Mixtures of Sparse Linear Classifiers with Fewer Measurements

    Sep 26, 2026Xiaxin Li, Arya MazumdarSparse RecoverySample Complexity

  13. Iterative Atom Refinement: A Monotonicity Principle for Dictionary Learning

    Sep 20, 2026Alexander Christie, Miguel Moscoso, Alexei Novikov +2Sparse RecoveryDictionary Learning

  14. Sparse Identification for Automatic Large-Scale Screening: A Constraint-Aware Framework with Ultra Fast Decoding Algorithm

    Sep 18, 2026Jianing Li, Li Chai, Yingcheng LaiSparse RecoveryMedical Diagnosis

  15. Diagonalized Attention for Individualized Regression: Latent-Row Localization and Prediction

    Sep 18, 2026Borui Peng, Liwei Lin, Feifei Wang +1Feature SelectionSparse Attention

  16. High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression

    Sep 8, 2026Syamantak Kumar, Purnamrita Sarkar, Kevin Tian +1Sparse RecoveryIsing Model

  17. Recovering linear images of sparse signals from indirect observations

    Sep 5, 2026Anatoli Juditsky, Arkadi NemirovskiSparse RecoveryCompressed Sensing

  18. Restricted Eigenvalues Beyond Gaussian Width: Threshold Occupancy under Heavy Tails

    Sep 3, 2026Shi Fu, Huibo Xu, Qixin Zhang +1Sparse RecoveryHeavy-Tailed Noise

  19. HarmoCore: Functional Latent Diffusion for Sparse Reconstruction of Oscillatory Wave Fields

    Sep 1, 2026Lihao Chen, Xinyu Zhang, Panqi Chen +4Sparse RecoveryLatent Diffusion Models

  20. Sharp Restricted Isometry Thresholds for Global Minima of Rank-Restricted Matrix LASSO

    Aug 29, 2026Richard Y. ZhangMatrix OptimizationSparse Recovery

  21. Towards a mathematical theory of superposition

    Aug 27, 2026Michael I. Ivanitskiy, John Jasper, Emily J. King +1Feature SuperpositionSparse Recovery

  22. Physical-Support Confidence Sets for Highly Coherent Dictionaries

    Aug 20, 2026Guan-Ju PengQuery IdentifiabilitySparse Recovery

  23. GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels

    Aug 19, 2026Rafid Umayer Murshed, Shahab Hamidi-Rad, Elahe Soltanaghai +1Wireless CommunicationsNeural Operators

  24. Online Generalized Sparse Regression: How Does Overparametrization Help?

    Aug 18, 2026Shuoguang Yang, Qiang SunOverparameterizationSparse Recovery

  25. Coded Hankel Polynomial Chaos: Spectral Identification of Dominant Polynomial-Chaos Modes

    Aug 17, 2026Zhiliang Deng, Xiaomei YangUncertainty QuantificationSpectral Methods

  26. Learning the Mathematical Property for Designing Low Mutual Coherence Binary Sensing Matrices

    Aug 13, 2026Rekha, Santosh Singh, S. K. NeogySparse RecoveryCompressed Sensing

  27. Robust data-driven discovery of fractional differential equations via weak formulations and Pareto-based subset selection

    Aug 13, 2026Pongpisit Thanasutives, Yoshinobu KawaharaSparse RecoveryPDE Discovery