**Preprints:**

- Solution Path of Time-varying Markov Random Fields with Discrete Regularization, submitted, 2023,

S. Fattahi and A. Gomez - Heterogeneous Matrix Factorization: When Features Differ by Datasets, submitted, 2023,

N. Shi, R. Al Kontar, and S. Fattahi - Robust Sparse Mean Estimation via Incremental Learning, submitted, 2023,

J. Ma, R. Ren Chen, Y. He, S. Fattahi, and W. Hu - Personalized Dictionary Learning for Heterogeneous Datasets, submitted, 2023,

G. Liang, N. Shi, R. Al Kontar, and S. Fattahi - On the Optimization Landscape of Burer-Monteiro Factorization: When do Global Solutions Correspond to Ground Truth?, submitted, 2023,

J. Ma and S. Fattahi - Simple Alternating Minimization Provably Solves Complete Dictionary Learning, submitted, 2022,

G. Liang, G. Zhang, S. Fattahi, and R. Y. Zhang

**Journal Papers:**

- Efficient Inference of Spatially-varying Gaussian Markov Random Fields with Applications in Gene Regulatory Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023,

V. Ravikumar, T. Xu, W. N. Al-Holou, S. Fattahi, and A. Rao - Preconditioned Gradient Descent for Overparameterized Nonconvex Burer–Monteiro Factorization with Global Optimality Certification, Journal of Machine Learning Research, 2023,

G. Zhang, S. Fattahi, and R. Y. Zhang - 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 - A Graph-based Decomposition Method for Convex Quadratic Optimization with Indicators, Mathematical Programming, 2022,

P. Liu, S. Fattahi, A. Gomez, and S. Küçükyavuz - Absence of Spurious Local Trajectories in Time-varying Optimization, to appear in IEEE Transactions on Automatic Control, 2021,

S. Fattahi, C. Josz, R. Mohammadi, J. Lavaei, and S. Sojoudi - Sample Complexity of Sparse System Identification, IEEE Transactions on Control of Network Systems, 2021,

S. Fattahi and S. Sojoudi - Smoothing Property of Load Variation Promotes Finding Global Solutions of Time-Varying Optimal Power Flow, IEEE Transactions on Control of Network Systems, 2021,

J. Mulvaney-Kemp, S. Fattahi, and J. Lavaei - Efficient Learning of Distributed Linear-Quadratic Controllers, SIAM Journal on Control and Optimization, 2020,

S. Fattahi, N. Matni, and S. Sojoudi - 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*. - Convexification of Generalized Network Flow Problem, Mathematical Programming, 2019,

S. Sojoudi, S. Fattahi and J. Lavaei - A Bound Strengthening Method for Optimal Transmission Switching in Power Systems, to appear in IEEE Transactions on Power Systems, 2019,

S. Fattahi, J. Lavaei and A. Atamturk - Linear-Time Algorithm for Learning Large-Scale Sparse Graphical Models, IEEE Access, 2019,

S. Fattahi and S. Sojoudi - Transformation of Optimal Centralized Controllers Into Near-Global Static Distributed Controllers, IEEE Transactions on Automatic Control, 2019,

S. Fattahi, G. Fazelnia and J. Lavaei - Conic Relaxation of the Unit Commitment Problem, Energy, 2017,

S. Fattahi, M. Ashraphijou, J. Lavaei and A. Atamturk

**Conference Papers:**

- Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition, International Conference on Learning Representations, 2023,

J. Ma, L. Guo, and S. Fattahi - Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution, Neural Information Processing Systems, Spotlight (top 3%), 2022,

J. Ma and S. Fattahi - Sign-RIP: A Robust Restricted Isometry Property for Low-rank Matrix Recovery, Neural Information Processing Systems, Workshop on Optimization for Machine Learning, 2021,

J. Ma and S. Fattahi - Preconditioned Gradient Descent for Over-parameterized Nonconvex Matrix Factorization, Neural Information Processing Systems, 2021,

G. Zhang, S. Fattahi, R.Y. Zhang - Scalable Inference of Sparsely-changing Gaussian Markov Random Fields, Neural Information Processing Systems, 2021,

S. Fattahi and A. Gomez - Learning Partially Observed Linear Dynamical Systems from Logarithmic Number of Samples, Learning for Dynamics & Control Conference, 2021,

S. Fattahi - Load Variation Enables Escaping Poor Solutions of Time-Varying Optimal Power Flow, IEEE Power & Energy Society General Meeting, 2020,

J. Mulvaney-Kemp, S. Fattahi, and J. Lavaei

*Best Conference Paper Award (one of multiple awards)* -
Learning Sparse Dynamical Systems from a Single Sample Trajectory, IEEE Conference on Decision and Control, 2019,

S. Fattahi, N. Matni, and S. Sojoudi -
Data-Driven Sparse System Identification, 56th Annual Allerton Conference on Communication, Control, and Computing, 2018

S. Fattahi and S. Sojoudi -
Non-Asymptotic Analysis of Block-Regularized Regression Problem, IEEE Conference on Decision and Control, 2018

S. Fattahi and S. Sojoudi -
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion, International Conference on Machine Learning, 2018

R. Y. Zhang, S. Fattahi and S. Sojoudi -
Sparse Inverse Covariance Estimation for Chordal Structures, European Control Conference, 2018

S. Fattahi, R. Y. Zhang and S. Sojoudi -
Closed-Form Solution and Sparsity Path for Inverse Covariance Estimation Problem, American Control Conference, 2018

S. Fattahi and S. Sojoudi

*Best Paper Award-Finalist*. -
High-Performance Cooperative Distributed Model Predictive Control for Linear Systems, American Control Conference, 2018

G. Darivianakis, S. Fattahi, J. Lygeros and J. Lavaei -
Promises of Conic Relaxations in Optimal Transmission Switching of Power Systems, IEEE Conference on Decision and Control,2017

S. Fattahi, J. Lavaei and A. Atamturk -
A Scalable Method for Designing Distributed Controllers for Systems with Unknown Initial States, IEEE Conference on Decision and Control, 2017

S. Fattahi, J. Lavaei and M. Arcak -
On the Convexity of Optimal Decentralized Control Problem and Sparsity Path, American Control Conference, 2017

S. Fattahi and J. Lavaei -
Theoretical Guarantees for the Design of Near Globally Optimal Static, 54th Annual Allerton Conference on Communication, Control, and Computing, 2016

S. Fattahi and J. Lavaei -
A Strong Semidefinite Programming Relaxation of the Unit Commitment Problem, IEEE Conference on Decision and Control, 2016

M. Ashraphijou, S. Fattahi, J. Lavaei and A. Atamturk -
Convex Analysis of Generalized Flow Networks, IEEE Conference on Decision and Control, 2015

S. Fattahi and J. Lavaei -
Transformation of Optimal Centralized Controllers Into Near-Global Static Distributed Controllers, IEEE Conference on Decision and Control, 2015

S. Fattahi, G. Fazelnia and J. Lavaei -
An Algorithm for Detecting Exact Regions of Moving Objects in Video Frames, International Symposium on Telecommunication, 2014

S. Fattahi, M. Azghani and F. Marvasti