- Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization, Journal of Machine Learning Research, 2023,
J. Ma and S. Fattahi - Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition, ICLR 2023,
Jianhao Ma, Lingjun Guo, and Salar Fattahi - Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution, NeurIPS 2022, Spotlight (top 3%),
Jianhao Ma and Salar Fattahi - A Graph-based Decomposition Method for Convex Quadratic Optimization with Indicators, Mathematical Programming, 2022,
P. Liu, S. Fattahi, A. Gomez, and S. Küçükyavuz
– INFORMS Computing Society Best Student Paper Award, 2022. - Preconditioned Gradient Descent for Over-parameterized Nonconvex Matrix Factorization, NeurIPS 2021,
G. Zhang, S. Fattahi, R.Y. Zhang - Scalable Inference of Sparsely-changing Gaussian Markov Random Fields, NeurIPS 2021,
S. Fattahi and A. Gomez - Exact Guarantees on the Absence of Spurious Local Minima for Non-negative Rank-1 Robust Principal Component Analysis, Journal of Machine Learning Research, 2020,
S. Fattahi and S. Sojoudi - Graphical Lasso and Thresholding: Equivalence and Closed-form Solutions, Journal of Machine Learning Research, 2019,
S. Fattahi and S. Sojoudi
– INFORMS Data Mining Best Paper Award, 2018.
– Katta G. Murty Best Paper Award, 2018. - Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion, ICML 2018,
R. Y. Zhang, S. Fattahi and S. Sojoudi