Greedy Sparsity-Constrained Optimization S Bahmani, B Raj, PT Boufounos Journal of Machine Learning Research 14 (3), 807-841, 2013 | 255 | 2013 |
Phase retrieval meets statistical learning theory: A flexible convex relaxation S Bahmani, J Romberg Artificial Intelligence and Statistics (AISTATS), International Conference
, 2017 | 150 | 2017 |
Efficient compressive phase retrieval with constrained sensing vectors S Bahmani, J Romberg Advances in Neural Information Processing Systems 28, 523-531, 2015 | 74 | 2015 |
Learning Model-Based Sparsity via Projected Gradient Descent S Bahmani, P Boufounos, B Raj Information Theory, IEEE Transactions on 62 (4), 2092--2099, 2016 | 38 | 2016 |
Lifting for Blind Deconvolution in Random Mask Imaging: Identifiability and Convex Relaxation S Bahmani, J Romberg SIAM Journal on Imaging Sciences 8 (4), 22032238, 2015 | 38 | 2015 |
A unifying analysis of Projected Gradient Descent for ℓp-constrained least squares S Bahmani, B Raj Applied and Computational Harmonic Analysis 34 (3), 366-378, 2013 | 34 | 2013 |
A flexible convex relaxation for phase retrieval S Bahmani, J Romberg Electronic Journal of Statistics 11 (2), 5254--5281, 2017 | 33 | 2017 |
Near-optimal estimation of simultaneously sparse and low-rank matrices from nested linear measurements S Bahmani, J Romberg Information and Inference: A Journal of the IMA 5 (3), 331-351, 2016 | 26 | 2016 |
Robust 1-bit compressive sensing via gradient support pursuit S Bahmani, PT Boufounos, B Raj arXiv preprint arXiv:1304.6627, 2013 | 23 | 2013 |
Solving equations of random convex functions via anchored regression S Bahmani, J Romberg Foundations of Computational Mathematics 19 (4), 813-841, 2019 | 20* | 2019 |
Compressive Deconvolution in Random Mask Imaging S Bahmani, J Romberg Computational Imaging, IEEE Transactions on 1 (4), 236--246, 2015 | 18 | 2015 |
Convex Programming for Estimation in Nonlinear Recurrent Models S Bahmani, J Romberg Journal of Machine Learning Research 21 (235), 1-20, 2020 | 16 | 2020 |
Sketching for simultaneously sparse and low-rank covariance matrices S Bahmani, J Romberg Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015
, 2015 | 14 | 2015 |
Algorithms for Sparsity-Constrained Optimization S Bahmani Carnegie Mellon University, 2013 | 13* | 2013 |
Joint decoding of unequally protected JPEG2000 bitstreams and Reed-Solomon codes S Bahmani, IV Bajic, A HajShirmohammadi Image Processing, IEEE Transactions on 19 (10), 2693-2704, 2010 | 7 | 2010 |
Joint source-chanel decoding of JPEG2000 images with unequal loss protection S Bahmani, IV Bajic, A HajShirMohammadi 2008 IEEE International Conference on Acoustics, Speech and Signal
, 2008 | 6 | 2008 |
Nearly optimal robust mean estimation via empirical characteristic function S Bahmani Bernoulli 27 (3), 2139-2158, 2021 | 5 | 2021 |
Phase retrieval of low-rank matrices by anchored regression K Lee, S Bahmani, YC Eldar, J Romberg Information and Inference: A Journal of the IMA 10 (1), 285-332, 2021 | 4 | 2021 |
Estimation from nonlinear observations via convex programming with application to bilinear regression S Bahmani Electronic Journal of Statistics 13 (1), 1978-2011, 2019 | 4 | 2019 |
Max-Linear Regression by Convex Programming S Kim, S Bahmani, K Lee IEEE Transactions on Information Theory, 2024 | 3* | 2024 |