Jason N. Laska

Computational Mechanics · 2006–2011

A researcher in the Science corpus: 8 papers; trusts 20 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 69 citations into it; #1,220 of 10,001 by trust here, #432 by citations
• Computer Vision and Pattern Recognition — 41 citations into it
• Applied Mathematics — 28 citations into it
• Biomedical Engineering — 27 citations into it; #1,299 of 10,734 by trust here, #2,129 by citations
• Signal Processing — 20 citations into it
• Optimization & Training — 17 citations into it
• Computer Networks and Communications — 10 citations into it; #5,265 of 9,886 by trust here, #5,133 by citations
• Radiology, Nuclear Medicine and Imaging — 7 citations into it; #2,076 of 3,265 by trust here, #1,081 by citations

Whom Jason N. Laska trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. E.J. Candes
2. Joel A. Tropp
3. Justin K. Romberg
4. David L. Donoho
5. Terence Tao
6. Richard Baraniuk
7. Thomas Strohmer
8. Robert Tibshirani
9. Anna C. Gilbert
10. Stéphane Mallat

Who trusts Jason N. Laska overall

1. Justin K. Romberg
2. Richard Baraniuk
3. Chengbo Li
4. Moshe Mishali
5. Marco F. Duarte
6. Yonina C. Eldar
7. Joel A. Tropp
8. Mark A. Davenport
9. Yaniv Plan
10. Surya Ganguli

Papers from Jason N. Laska's perspective

Ordered by how strongly the researchers Jason N. Laska trusts endorse each paper. Same corpus, a different order for every researcher.

1. Regression Shrinkage and Selection via the Lasso
2. Atomic Decomposition by Basis Pursuit
3. Stable signal recovery from incomplete and inaccurate measurements
4. Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
5. Decoding by linear programming
6. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples (arXiv.org)
7. Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems (IEEE Journal on Selected Topics in Signal Processing)
8. A Simple Proof of the Restricted Isometry Property for Random Matrices
9. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
10. The Dantzig selector: Statistical estimation when P is much larger than n

Their papers

• Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals (2009) — 1,096 citations
• Analog-to-Information Conversion via Random Demodulation (2006) — 428 citations
• A new compressive imaging camera architecture using optical-domain compression (2006) — 641 citations
• Theory and Implementation of an Analog-to-Information Converter using Random Demodulation (2007) — 447 citations
• An Architecture for Compressive Imaging (2006) — 373 citations
• The smashed filter for compressive classification and target recognition (2007) — 307 citations
• Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors (2011) — 690 citations
• Single-pixel imaging via compressive sampling (2008) — 3,542 citations