Mahdi Soltanolkotabi
Title
Cited by
Cited by
Year
Phase retrieval via Wirtinger flow: Theory and algorithms
EJ Candes, X Li, M Soltanolkotabi
IEEE Transactions on Information Theory 61 (4), 1985-2007, 2015
9862015
Discussion of "Latent Variable Graphical Model Selection via Convex Optimization"
EJCM Soltanolkotabi
Annals of Statistics 40 (2), 1997-2004, 2012
488*2012
A geometric analysis of subspace clustering with outliers
M Soltanolkotabi, EJ Candes
The Annals of Statistics 40 (4), 2195-2238, 2012
4282012
Robust subspace clustering
M Soltanolkotabi, E Elhamifar, EJ Candes
Annals of Statistics 42 (2), 669-699, 2014
3592014
Phase Retrieval from Coded Diffraction Patterns
E Candes, X Li, M Soltanolkotabi
Applied and Computational Harmonic Analysis, 2013
3312013
Low-rank solutions of linear matrix equations via procrustes flow
S Tu, R Boczar, M Soltanolkotabi, B Recht
Proceedings of International Conference on Machine Learning, 2016
2942016
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks
M Soltanolkotabi, A Javanmard, JD Lee
arXiv preprint arXiv:1707.04926, 2018
2482018
Experimental robustness of Fourier ptychography phase retrieval algorithms
LH Yeh, J Dong, J Zhong, L Tian, M Chen, G Tang, M Soltanolkotabi, ...
Optics express 23 (26), 33214-33240, 2015
1822015
Lagrange coded computing: Optimal design for resiliency, security, and privacy
Q Yu, S Li, N Raviv, SMM Kalan, M Soltanolkotabi, SA Avestimehr
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
1422019
A unified approach to sparse signal processing
F Marvasti, A Amini, F Haddadi, M Soltanolkotabi, BH Khalaj, A Aldroubi, ...
EURASIP journal on advances in signal processing 2012 (1), 1-45, 2012
1322012
Toward Moderate Overparameterization: Global Convergence Guarantees for Training Shallow Neural Networks
S Oymak, M Soltanolkotabi
IEEE Journal on Selected Areas in Information Theory 1 (1), 84-105, 2020
1242020
Learning relus via gradient descent
M Soltanolkotabi
arXiv preprint arXiv:1705.04591, 2017
1102017
Sharp Time--Data Tradeoffs for Linear Inverse Problems
S Oymak, B Recht, M Soltanolkotabi
arXiv preprint arXiv:1507.04793, 2017
902017
Compressed sensing with deep image prior and learned regularization
D Van Veen, A Jalal, M Soltanolkotabi, E Price, S Vishwanath, ...
arXiv preprint arXiv:1806.06438, 2018
822018
Structured signal recovery from quadratic measurements: Breaking sample complexity barriers via nonconvex optimization
M Soltanolkotabi
arXiv preprint arXiv:1702.06175, 2018
782018
Gradient descent with early stopping is provably robust to label noise for overparameterized neural networks
M Li, M Soltanolkotabi, S Oymak
International Conference on Artificial Intelligence and Statistics, 4313-4324, 2020
772020
Overparameterized nonlinear learning: Gradient descent takes the shortest path?
S Oymak, M Soltanolkotabi
International Conference on Machine Learning, 4951-4960, 2019
762019
Gradient methods for submodular maximization
H Hassani, M Soltanolkotabi, A Karbasi
arXiv preprint arXiv:1708.03949, 2017
742017
Super-resolution radar
R Heckel, VI Morgenshtern, M Soltanolkotabi
http://imaiai.oxfordjournals.org/content/early/2016/02/23/imaiai.iaw001, 2016
732016
Near-Optimal Straggler Mitigation for Distributed Gradient Methods
S Li, SMM Kalan, AS Avestimehr, M Soltanolkotabi
arXiv preprint arXiv:1710.09990, 2018
632018
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