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Publications of S. Hassan-Moghaddam
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S. Hassan-Moghaddam.
Analysis, design, and optimization of large-scale networks of dynamical systems.
PhD thesis,
University of Southern California,
2019.
Keyword(s): Consensus,
Control for optimization,
Convex Optimization,
Distributed control,
Forward-backward envelope,
Douglas-Rachford splitting,
Global exponential stability,
Integral quadratic constraints,
Networks of dynamical systems,
Non-smooth optimization,
Polyak-Lojasiewicz inequality,
Proximal algorithms,
Primal-dual methods,
Proximal augmented Lagrangian,
Regularization for design,
Sparse graphs,
Sparsity-promoting optimal control,
Structured optimal control,
Structure identification,
Topology design.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
Proximal gradient flow and Douglas-Rachford splitting dynamics: global exponential stability via integral quadratic constraints.
Automatica,
123:109311,
January 2021.
Keyword(s): Control for optimization,
Convex Optimization,
Forward-backward envelope,
Douglas-Rachford splitting,
Global exponential stability,
Integral quadratic constraints,
Non-smooth optimization,
Polyak-Lojasiewicz inequality,
Proximal algorithms,
Primal-dual methods,
Proximal augmented Lagrangian.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
Topology design for stochastically-forced consensus networks.
IEEE Trans. Control Netw. Syst.,
5(3):1075-1086,
September 2018.
Keyword(s): Consensus,
Convex optimization,
Distributed control,
Interior point method,
Proximal gradient method,
Proximal Newton method,
Sparse graphs,
Topology design.
[bibtex-entry]
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I. K. Ozaslan,
S. Hassan-Moghaddam,
and M. R. Jovanovic.
On the asymptotic stability of proximal algorithms for convex optimization problems with multiple non-smooth regularizers.
In Proceedings of the 2022 American Control Conference,
Atlanta, GA,
pages 132-137,
2022.
Keyword(s): Control for optimization,
Convex Optimization,
Douglas-Rachford splitting,
Global asymptotic stability,
Lyapunov-based analysis,
Non-smooth optimization,
Proximal algorithms,
Primal-dual gradient flow dynamics,
Primal-dual methods,
Proximal augmented Lagrangian.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
Global exponential stability of the Douglas-Rachford splitting dynamics.
In Preprints of the 21st IFAC World Congress,
Berlin, Germany,
pages 7350-7354,
2020.
Keyword(s): Control for optimization,
Convex Optimization,
Forward-backward envelope,
Douglas-Rachford splitting,
Global exponential stability,
Integral quadratic constraints,
Non-smooth optimization,
Polyak-Lojasiewicz inequality,
Proximal algorithms,
Primal-dual methods,
Proximal augmented Lagrangian.
[bibtex-entry]
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S. Hassan-Moghaddam,
M. R. Jovanovic,
and S. Meyn.
Data-driven proximal algorithms for the design of structured optimal feedback gains.
In Proceedings of the 2019 American Control Conference,
Philadelphia, PA,
pages 5846-5850,
2019.
Keyword(s): Data-driven feedback design,
Large-scale systems,
Non-smooth optimization,
Proximal algorithms,
Reinforcement learning,
Sparsity-promoting optimal control,
Structured optimal control.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
Distributed proximal augmented Lagrangian method for nonsmooth composite optimization.
In Proceedings of the 2018 American Control Conference,
Milwaukee, WI,
pages 2047-2052,
2018.
Keyword(s): Consensus,
Distributed Optimization,
Non-smooth optimization,
Primal-dual gradient flow dynamics,
Proximal augmented Lagrangian.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
On the exponential convergence rate of proximal gradient flow algorithms.
In Proceedings of the 57th IEEE Conference on Decision and Control,
Miami, FL,
pages 4246-4251,
2018.
Note: (Invited paper).
Keyword(s): Control for optimization,
Distributed optimization,
Forward-backward envelope,
Exponential convergence,
Global exponential stability,
Gradient flow dynamics,
Large-scale systems,
Non-smooth optimization,
Primal-dual method,
Proximal algorithms,
Proximal augmented Lagrangian.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
Topology identification via growing a Chow-Liu tree network.
In Proceedings of the 57th IEEE Conference on Decision and Control,
Miami, FL,
pages 5421-5426,
2018.
Keyword(s): Chow-Liu tree,
Consensus,
Convex optimization,
Graphical LASSO,
Sparse graphs,
Topology identification,
Maximum likelihood,
Sparse inverse covariance estimation.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
Distributed design of optimal structured feedback gains.
In Proceedings of the 56th IEEE Conference on Decision and Control,
Melbourne, Australia,
pages 6586-6591,
2017.
Keyword(s): Alternating direction method of multipliers,
Consensus,
Distributed control,
Optimization,
Sparsity-promoting optimal control,
Structured optimal control.
[bibtex-entry]
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S. Hassan-Moghaddam,
X. Wu,
and M. R. Jovanovic.
Edge addition in directed consensus networks.
In Proceedings of the 2017 American Control Conference,
Seattle, WA,
pages 5592-5597,
2017.
Keyword(s): Alternating direction method of multipliers,
Consensus,
Directed networks,
Nonconvex optimization,
Sparsity-promoting optimal control.
[bibtex-entry]
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S. Hassan-Moghaddam,
N. K. Dhingra,
and M. R. Jovanovic.
Topology identification of undirected consensus networks via sparse inverse covariance estimation.
In Proceedings of the 55th IEEE Conference on Decision and Control,
Las Vegas, NV,
pages 4624-4629,
2016.
Keyword(s): Consensus,
Convex optimization,
Sparse graphs,
Topology identification,
Maximum likelihood,
Sparse inverse covariance estimation.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
Customized algorithms for growing connected resistive networks.
In Proceedings of the 10th IFAC Symposium on Nonlinear Control Systems,
Monterey, CA,
pages 986-991,
2016.
Keyword(s): Convex optimization,
Coordinate descent algorithm,
Networks,
Proximal algorithms.
[bibtex-entry]
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S. Hassan-Moghaddam and M. R. Jovanovic.
An interior point method for growing connected resistive networks.
In Proceedings of the 2015 American Control Conference,
Chicago, IL,
pages 1223-1228,
2015.
Keyword(s): Consensus,
Convex optimization,
Distributed control,
Interior point method,
Sparse graphs,
Topology design.
[bibtex-entry]
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