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Publications of S. HassanMoghaddam


S. HassanMoghaddam.
Analysis, design, and optimization of largescale networks of dynamical systems.
PhD thesis,
University of Southern California,
2019.
Keyword(s): Consensus,
Control for optimization,
Convex Optimization,
Distributed control,
Forwardbackward envelope,
DouglasRachford splitting,
Global exponential stability,
Integral quadratic constraints,
Networks of dynamical systems,
Nonsmooth optimization,
PolyakLojasiewicz inequality,
Proximal algorithms,
Primaldual methods,
Proximal augmented Lagrangian,
Regularization for design,
Sparse graphs,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification,
Topology design.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Proximal gradient flow and DouglasRachford splitting dynamics: global exponential stability via integral quadratic constraints.
Automatica,
123:109311,
January 2021.
Keyword(s): Control for optimization,
Convex Optimization,
Forwardbackward envelope,
DouglasRachford splitting,
Global exponential stability,
Integral quadratic constraints,
Nonsmooth optimization,
PolyakLojasiewicz inequality,
Proximal algorithms,
Primaldual methods,
Proximal augmented Lagrangian.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Topology design for stochasticallyforced consensus networks.
IEEE Trans. Control Netw. Syst.,
5(3):10751086,
September 2018.
Keyword(s): Consensus,
Convex optimization,
Distributed control,
Interior point method,
Proximal gradient method,
Proximal Newton method,
Sparse graphs,
Topology design.
[bibtexentry]

I. K. Ozaslan,
S. HassanMoghaddam,
and M. R. Jovanovic.
On the asymptotic stability of proximal algorithms for convex optimization problems with multiple nonsmooth regularizers.
In Proceedings of the 2022 American Control Conference,
Atlanta, GA,
2022.
Note: To appear.
Keyword(s): Control for optimization,
Convex Optimization,
DouglasRachford splitting,
Global asymptotic stability,
Lyapunovbased analysis,
Nonsmooth optimization,
Proximal algorithms,
Primaldual gradient flow dynamics,
Primaldual methods,
Proximal augmented Lagrangian.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Global exponential stability of the DouglasRachford splitting dynamics.
In Preprints of the 21st IFAC World Congress,
Berlin, Germany,
pages 73507354,
2020.
Keyword(s): Control for optimization,
Convex Optimization,
Forwardbackward envelope,
DouglasRachford splitting,
Global exponential stability,
Integral quadratic constraints,
Nonsmooth optimization,
PolyakLojasiewicz inequality,
Proximal algorithms,
Primaldual methods,
Proximal augmented Lagrangian.
[bibtexentry]

S. HassanMoghaddam,
M. R. Jovanovic,
and S. Meyn.
Datadriven proximal algorithms for the design of structured optimal feedback gains.
In Proceedings of the 2019 American Control Conference,
Philadelphia, PA,
pages 58465850,
2019.
Keyword(s): Datadriven feedback design,
Largescale systems,
Nonsmooth optimization,
Proximal algorithms,
Reinforcement learning,
Sparsitypromoting optimal control,
Structured optimal control.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Distributed proximal augmented Lagrangian method for nonsmooth composite optimization.
In Proceedings of the 2018 American Control Conference,
Milwaukee, WI,
pages 20472052,
2018.
Keyword(s): Consensus,
Distributed Optimization,
Nonsmooth optimization,
Primaldual gradient flow dynamics,
Proximal augmented Lagrangian.
[bibtexentry]

S. HassanMoghaddam 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 42464251,
2018.
Note: (Invited paper).
Keyword(s): Control for optimization,
Distributed optimization,
Forwardbackward envelope,
Exponential convergence,
Global exponential stability,
Gradient flow dynamics,
Largescale systems,
Nonsmooth optimization,
Primaldual method,
Proximal algorithms,
Proximal augmented Lagrangian.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Topology identification via growing a ChowLiu tree network.
In Proceedings of the 57th IEEE Conference on Decision and Control,
Miami, FL,
pages 54215426,
2018.
Keyword(s): ChowLiu tree,
Consensus,
Convex optimization,
Graphical LASSO,
Sparse graphs,
Topology identification,
Maximum likelihood,
Sparse inverse covariance estimation.
[bibtexentry]

S. HassanMoghaddam 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 65866591,
2017.
Keyword(s): Alternating direction method of multipliers,
Consensus,
Distributed control,
Optimization,
Sparsitypromoting optimal control,
Structured optimal control.
[bibtexentry]

S. HassanMoghaddam,
X. Wu,
and M. R. Jovanovic.
Edge addition in directed consensus networks.
In Proceedings of the 2017 American Control Conference,
Seattle, WA,
pages 55925597,
2017.
Keyword(s): Alternating direction method of multipliers,
Consensus,
Directed networks,
Nonconvex optimization,
Sparsitypromoting optimal control.
[bibtexentry]

S. HassanMoghaddam,
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 46244629,
2016.
Keyword(s): Consensus,
Convex optimization,
Sparse graphs,
Topology identification,
Maximum likelihood,
Sparse inverse covariance estimation.
[bibtexentry]

S. HassanMoghaddam 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 986991,
2016.
Keyword(s): Convex optimization,
Coordinate descent algorithm,
Networks,
Proximal algorithms.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
An interior point method for growing connected resistive networks.
In Proceedings of the 2015 American Control Conference,
Chicago, IL,
pages 12231228,
2015.
Keyword(s): Consensus,
Convex optimization,
Distributed control,
Interior point method,
Sparse graphs,
Topology design.
[bibtexentry]
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