Wei Dai

Computational Mechanics · with Milenkovic · 2006–2008

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 21 citations into it; #2,291 of 10,001 by trust here, #4,749 by citations
• Signal Processing — 9 citations into it; #1,878 of 7,572 by trust here, #3,784 by citations
• Computer Vision and Pattern Recognition — 8 citations into it
• Biomedical Engineering — 5 citations into it; #1,453 of 10,734 by trust here, #6,773 by citations

Whom Wei Dai trusts overall

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

1. E.J. Candes
2. Joel A. Tropp
3. Terence Tao
4. Deanna Needell
5. Paul Tseng
6. Roman Vershynin
7. Yurii E. Nesterov
8. Mark Rudelson
9. Sangwoon Yun
10. David L. Donoho

Who trusts Wei Dai overall

1. Simon Foucart
2. Marco F. Duarte
3. Kiryung Lee
4. Thomas Blumensath
5. Deanna Needell
6. Thong T. Do
7. Mark A. Davenport
8. Alireza Doostan
9. David L. Donoho
10. Xiongbin Rao

Papers from Wei Dai's perspective

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

1. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
2. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples (arXiv.org)
3. Decoding by linear programming
4. Stable signal recovery from incomplete and inaccurate measurements
5. Uncertainty principles and ideal atomic decomposition
6. Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
7. Atomic Decomposition by Basis Pursuit
8. Signal Recovery From Incomplete and Inaccurate Measurements Via Regularized Orthogonal Matching Pursuit (IEEE Journal on Selected Topics in Signal Processing)
9. Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems (IEEE Journal on Selected Topics in Signal Processing)
10. Regression Shrinkage and Selection via the Lasso

Their papers

• Subspace Pursuit for Compressive Sensing Signal Reconstruction (2008) — 911 citations
• Subspace Pursuit for Compressive Sensing: Closing the Gap Between Performance and Complexity (2008) — 1,698 citations
• 2006 IEEE International Symposium on Information Theory (2006) — 558 citations