# Sparse and Compressive Sensing Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/sparse-and-compressive-sensing-techniques/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the theory and applications of compressed sensing, including sparse representation, signal recovery, convex optimization, matrix completion, dictionary learning, orthogonal matching pursuit, robust reconstruction, and sparsity in signal processing. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | t10500 |
| Works | 52 |

## Topic papers all

Showing 15 of 52.

- [Regularization Paths for Generalized Linear Models via Coordinate Descent](https://scholariq.org/papers/regularization-paths-for-generalized-linear-models-via-coordinate-descent/)
- [Single-pixel imaging via compressive sampling](https://scholariq.org/papers/single-pixel-imaging-via-compressive-sampling/)
- [A Simple Proof of the Restricted Isometry Property for Random Matrices](https://scholariq.org/papers/a-simple-proof-of-the-restricted-isometry-property-for-random-matrices/)
- [Online Learning for Matrix Factorization and Sparse Coding](https://scholariq.org/papers/online-learning-for-matrix-factorization-and-sparse-coding/)
- [Online dictionary learning for sparse coding](https://scholariq.org/papers/online-dictionary-learning-for-sparse-coding/)
- [Sparse Representation for Computer Vision and Pattern Recognition](https://scholariq.org/papers/sparse-representation-for-computer-vision-and-pattern-recognition/)
- [Sparse Representation for Color Image Restoration](https://scholariq.org/papers/sparse-representation-for-color-image-restoration/)
- [Non-local sparse models for image restoration](https://scholariq.org/papers/non-local-sparse-models-for-image-restoration/)
- [Signal Processing With Compressive Measurements](https://scholariq.org/papers/signal-processing-with-compressive-measurements/)
- [Analysis of Orthogonal Matching Pursuit Using the Restricted Isometry Property](https://scholariq.org/papers/analysis-of-orthogonal-matching-pursuit-using-the-restricted-isometry-property/)
- [Sparse Coding via Thresholding and Local Competition in Neural Circuits](https://scholariq.org/papers/sparse-coding-via-thresholding-and-local-competition-in-neural-circuits/)
- [On Unifying Multi-view Self-Representations for Clustering by Tensor Multi-rank Minimization](https://scholariq.org/papers/on-unifying-multi-view-self-representations-for-clustering-by-tensor-multi-rank/)
- [Introduction to compressed sensing](https://scholariq.org/papers/introduction-to-compressed-sensing/)
- [Group sparse regularization for deep neural networks](https://scholariq.org/papers/group-sparse-regularization-for-deep-neural-networks/)
- [An Overview of Low-Rank Matrix Recovery From Incomplete Observations](https://scholariq.org/papers/an-overview-of-low-rank-matrix-recovery-from-incomplete-observations/)

## Topic primary papers

Showing 15 of 26.

- [Single-pixel imaging via compressive sampling](https://scholariq.org/papers/single-pixel-imaging-via-compressive-sampling/)
- [A Simple Proof of the Restricted Isometry Property for Random Matrices](https://scholariq.org/papers/a-simple-proof-of-the-restricted-isometry-property-for-random-matrices/)
- [Online Learning for Matrix Factorization and Sparse Coding](https://scholariq.org/papers/online-learning-for-matrix-factorization-and-sparse-coding/)
- [Online dictionary learning for sparse coding](https://scholariq.org/papers/online-dictionary-learning-for-sparse-coding/)
- [Sparse Representation for Computer Vision and Pattern Recognition](https://scholariq.org/papers/sparse-representation-for-computer-vision-and-pattern-recognition/)
- [Signal Processing With Compressive Measurements](https://scholariq.org/papers/signal-processing-with-compressive-measurements/)
- [Analysis of Orthogonal Matching Pursuit Using the Restricted Isometry Property](https://scholariq.org/papers/analysis-of-orthogonal-matching-pursuit-using-the-restricted-isometry-property/)
- [Introduction to compressed sensing](https://scholariq.org/papers/introduction-to-compressed-sensing/)
- [Group sparse regularization for deep neural networks](https://scholariq.org/papers/group-sparse-regularization-for-deep-neural-networks/)
- [An Overview of Low-Rank Matrix Recovery From Incomplete Observations](https://scholariq.org/papers/an-overview-of-low-rank-matrix-recovery-from-incomplete-observations/)
- [Construction of a Large Class of Deterministic Sensing Matrices That Satisfy a Statistical Isometry Property](https://scholariq.org/papers/construction-of-a-large-class-of-deterministic-sensing-matrices-that-satisfy-a/)
- [Chirp sensing codes: Deterministic compressed sensing measurements for fast recovery](https://scholariq.org/papers/chirp-sensing-codes-deterministic-compressed-sensing-measurements-for-fast/)
- [The smashed filter for compressive classification and target recognition](https://scholariq.org/papers/the-smashed-filter-for-compressive-classification-and-target-recognition/)
- [Democracy in action: Quantization, saturation, and compressive sensing](https://scholariq.org/papers/democracy-in-action-quantization-saturation-and-compressive-sensing/)
- [Robust Matrix Factorization with Unknown Noise](https://scholariq.org/papers/robust-matrix-factorization-with-unknown-noise/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.