Mahdi Soltanolkotabi
Cited by
Cited by
Phase retrieval via Wirtinger flow: Theory and algorithms
EJ Candes, X Li, M Soltanolkotabi
IEEE Transactions on Information Theory 61 (4), 1985-2007, 2015
Discussion of "Latent Variable Graphical Model Selection via Convex Optimization"
EJCM Soltanolkotabi
Annals of Statistics 40 (2), 1997-2004, 2012
A geometric analysis of subspace clustering with outliers
M Soltanolkotabi, EJ Candes
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks
M Soltanolkotabi, A Javanmard, JD Lee
arXiv preprint arXiv:1707.04926, 2018
Phase Retrieval from Coded Diffraction Patterns
E Candes, X Li, M Soltanolkotabi
Applied and Computational Harmonic Analysis, 2013
Robust subspace clustering
M Soltanolkotabi, E Elhamifar, EJ Candes
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
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
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
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
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
A field guide to federated optimization
J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ...
arXiv preprint arXiv:2107.06917, 2021
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
Overparameterized nonlinear learning: Gradient descent takes the shortest path?
S Oymak, M Soltanolkotabi
International Conference on Machine Learning, 4951-4960, 2019
Learning relus via gradient descent
M Soltanolkotabi
Advances in neural information processing systems 30, 2017
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, 1-45, 2012
Gradient methods for submodular maximization
H Hassani, M Soltanolkotabi, A Karbasi
Advances in Neural Information Processing Systems 30, 2017
Convergence and sample complexity of gradient methods for the model-free linear–quadratic regulator problem
H Mohammadi, A Zare, M Soltanolkotabi, MR Jovanović
IEEE Transactions on Automatic Control 67 (5), 2435-2450, 2021
Structured signal recovery from quadratic measurements: Breaking sample complexity barriers via nonconvex optimization
M Soltanolkotabi
arXiv preprint arXiv:1702.06175, 2018
Precise tradeoffs in adversarial training for linear regression
A Javanmard, M Soltanolkotabi, H Hassani
Conference on Learning Theory, 2034-2078, 2020
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