| Compressed sensing: theory and applications YC Eldar, G Kutyniok Cambridge University Press, 2012 | 3103 | 2012 |
| Efficient and robust compressed sensing using optimized expander graphs S Jafarpour, W Xu, B Hassibi, R Calderbank Information Theory, IEEE Transactions, 2009 | 246 | 2009 |
| Efficient compressive sensing with deterministic guarantees using expander graphs W Xu, B Hassibi 2007 IEEE Information Theory Workshop, 414-419, 2007 | 226 | 2007 |
| Weighted Minimization for Sparse Recovery with Prior Information MA Khajehnejad, W Xu, S Avestimehr, B Hassibi Arxiv preprint arXiv:0901.2912, 2009 | 220* | 2009 |
| Necessary and sufficient conditions for success of the nuclear norm heuristic for rank minimization B Recht, W Xu, B Hassibi 2008 47th IEEE Conference on Decision and Control, 3065-3070, 2008 | 176 | 2008 |
| Null space conditions and thresholds for rank minimization B Recht, W Xu, B Hassibi Mathematical Programming, 1-28, 2011 | 167 | 2011 |
| Compressive sensing over graphs W Xu, E Mallada, A Tang INFOCOM, 2011 Proceedings IEEE, 2087-2095, 2011 | 147 | 2011 |
| Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI T Liu, W Xu, P Spincemaille, AS Avestimehr, Y Wang IEEE transactions on medical imaging 31 (3), 816-824, 2012 | 143 | 2012 |
| Analyzing Weighted Minimization for Sparse Recovery With Nonuniform Sparse Models MA Khajehnejad, W Xu, AS Avestimehr, B Hassibi Signal Processing, IEEE Transactions on 59 (5), 1985-2001, 2011 | 133 | 2011 |
| Analyzing Weighted Minimization for Sparse Recovery with Nonuniform Sparse Models\ footnote {The results of this paper were presented in part at the … M Amin Khajehnejad, W Xu, A Salman Avestimehr, B Hassibi arXiv preprint arXiv:1009.3525, 2010 | 133* | 2010 |
| Sparse recovery of nonnegative signals with minimal expansion MA Khajehnejad, AG Dimakis, W Xu, B Hassibi Signal Processing, IEEE Transactions on 59 (1), 196-208, 2011 | 112 | 2011 |
| A unique “nonnegative” solution to an underdetermined system: From vectors to matrices M Wang, W Xu, A Tang IEEE Transactions on Signal Processing 59 (3), 1007-1016, 2011 | 107 | 2011 |
| A Unique “Nonnegative” Solution to an Underdetermined System: From Vectors to Matrices M Wang, W Xu, A Tang Signal Processing, IEEE Transactions on 59 (3), 1007-1016, 2011 | 107 | 2011 |
| Compressed sensing over the grassmann manifold: A unified analytical framework W Xu, B Hassibi Communication, Control, and Computing, 2008 46th Annual Allerton Conference …, 2008 | 94 | 2008 |
| Robust recovery of complex exponential signals from random Gaussian projections via low rank Hankel matrix reconstruction JF Cai, X Qu, W Xu, GB Ye Applied and Computational Harmonic Analysis, 2016 | 90 | 2016 |
| Precise semidefinite programming formulation of atomic norm minimization for recovering d-dimensional (d≥ 2) off-the-grid frequencies W Xu, JF Cai, KV Mishra, M Cho, A Kruger Information Theory and Applications Workshop (ITA), 2014, 1-4, 2014 | 89 | 2014 |
| Sparse error correction from nonlinear measurements with applications in bad data detection for power networks W Xu, M Wang, JF Cai, A Tang IEEE Transactions on Signal Processing 61 (24), 6175-6187, 2013 | 87* | 2013 |
| Spectral super-resolution with prior knowledge KV Mishra, M Cho, A Kruger, W Xu IEEE Transactions on Signal Processing 63 (20), 5342-5357, 2015 | 83 | 2015 |
| Compressed sensing-probabilistic analysis of a null-space characterization M Stojnic, W Xu, B Hassibi Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE …, 2008 | 80 | 2008 |
| On the Performance of Sparse Recovery Via -Minimization M Wang, W Xu, A Tang IEEE Transactions on Information Theory 57 (11), 7255-7278, 2011 | 76 | 2011 |
