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Publications about 'Lagrangian'


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]

N. K. Dhingra.
Optimization and control of largescale networked systems.
PhD thesis,
University of Minnesota,
2017.
Keyword(s): Augmented Lagrangian,
Combination drug therapy,
Convex optimization,
Directed networks,
Leader selection,
Method of multipliers,
Nonsmooth optimization,
Optimization,
Proximal algorithms,
Proximal augmented Lagrangian,
Regularization,
Second order primaldual method,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification.
[bibtexentry]

N. K. Dhingra,
S. Z. Khong,
and M. R. Jovanovic.
A second order primaldual method for nonsmooth convex composite optimization.
IEEE Trans. Automat. Control,
67(8):40614076,
August 2022.
Keyword(s): Augmented Lagrangian,
Exponential convergence,
Global exponential stability,
Method of multipliers,
Nonsmooth optimization,
Proximal algorithms,
Proximal augmented Lagrangian,
Regularization for design,
Second order primaldual method,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification.
[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]

A. Zare,
H. Mohammadi,
N. K. Dhingra,
T. T. Georgiou,
and M. R. Jovanovic.
Proximal algorithms for largescale statistical modeling and sensor/actuator selection.
IEEE Trans. Automat. Control,
65(8):34413456,
August 2020.
Keyword(s): Actuator selection,
Augmented Lagrangian,
Convex optimization,
Lowrank perturbation,
Matrix completion problem,
Method of multipliers,
Nonsmooth optimization,
Proximal algorithms,
Regularization for design,
Sensor selection,
Sparsitypromoting optimal control,
Structured covariances.
[bibtexentry]

N. K. Dhingra,
S. Z. Khong,
and M. R. Jovanovic.
The proximal augmented Lagrangian method for nonsmooth composite optimization.
IEEE Trans. Automat. Control,
64(7):28612868,
July 2019.
Keyword(s): Augmented Lagrangian,
Control for optimization,
Exponential convergence,
Global exponential stability,
Method of multipliers,
Nonsmooth optimization,
Primaldual gradient flow dynamics,
Proximal algorithms,
Proximal augmented Lagrangian,
Regularization for design,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification.
[bibtexentry]

F. Lin,
M. Fardad,
and M. R. Jovanovic.
Augmented Lagrangian approach to design of structured optimal state feedback gains.
IEEE Trans. Automat. Control,
56(12):29232929,
December 2011.
Keyword(s): Architectural issues in distributed control design,
Distributed control,
Optimal localized control.
[bibtexentry]

D. Ding,
X. Wei,
Z. Yang,
Z. Wang,
and M. R. Jovanovic.
Provably efficient generalized Lagrangian policy optimization for safe multiagent reinforcement learning.
In Proceedings of 5th Annual Conference on Learning for Dynamics and Control,
volume 211 of Proceedings of Machine Learning Research,
Philadelphia, PA,
pages 315332,
2023.
Keyword(s): Constrained Markov games,
Method of Lagrange multipliers,
Minimax optimization,
Multiagent reinforcement learning,
Primaldual policy optimization.
[bibtexentry]

I. K. Ozaslan and M. R. Jovanovic.
On the global exponential stability of primaldual dynamics for convex problems with linear equality constraints.
In Proceedings of the 2023 American Control Conference,
San Diago, CA,
pages 210215,
2023.
Keyword(s): Global exponential stability,
Gradient flow dynamics,
Lagrangian,
Lyapunov functions,
Primaldual methods.
[bibtexentry]

H. Mohammadi and M. R. Jovanovic.
On the noise amplification of primaldual gradient flow dynamics based on proximal augmented Lagrangian.
In Proceedings of the 2022 American Control Conference,
Atlanta, GA,
pages 926931,
2022.
Keyword(s): Control for optimization,
Convex Optimization,
Integral quadratic constraints,
Linear matrix inequalities,
Noise amplification,
Nonsmooth optimization,
Proximal algorithms,
Primaldual gradient flow dynamics,
Primaldual methods,
Proximal augmented Lagrangian,
Secondorder moments,
Semidefinite programming.
[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,
pages 132137,
2022.
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]

I. K. Ozaslan and M. R. Jovanovic.
Exponential convergence of primaldual dynamics for multiblock problems under local error bound condition.
In Proceedings of the 61th IEEE Conference on Decision and Control,
Cancun, Mexico,
pages 75797584,
2022.
Keyword(s): Gradient flow dynamics,
Lyapunov functions,
Proximal algorithms,
Primaldual gradient flow dynamics,
Primaldual methods,
Proximal augmented Lagrangian,
Operator splitting.
[bibtexentry]

D. Ding and M. R. Jovanovic.
Global exponential stability of primaldual gradient flow dynamics based on the proximal augmented Lagrangian: A Lyapunovbased approach.
In Proceedings of the 59th IEEE Conference on Decision and Control,
Jeju Island, Republic of Korea,
pages 48364841,
2020.
Keyword(s): Augmented Lagrangian,
Control for optimization,
Convex optimization,
Global exponential stability,
Lyapunovbased approach,
Nonsmooth optimization,
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]

D. Ding and M. R. Jovanovic.
Global exponential stability of primaldual gradient flow dynamics based on the proximal augmented Lagrangian.
In Proceedings of the 2019 American Control Conference,
Philadelphia, PA,
pages 34143419,
2019.
Keyword(s): Convex optimization,
Global exponential stability,
Nonsmooth optimization,
Primaldual gradient flow dynamics,
Proximal augmented Lagrangian method.
[bibtexentry]

D. Ding,
B. Hu,
N. K. Dhingra,
and M. R. Jovanovic.
An exponentially convergent primaldual algorithm for nonsmooth composite minimization.
In Proceedings of the 57th IEEE Conference on Decision and Control,
Miami, FL,
pages 49274932,
2018.
Keyword(s): Control for optimization,
Convex optimization,
Euler discretization,
Exponential convergence,
Global exponential stability,
Integral quadratic constraints,
Proximal augmented Lagrangian,
Nonsmooth optimization,
Primaldual gradient flow dynamics,
Proximal algorithms,
Regularization.
[bibtexentry]

D. Ding and M. R. Jovanovic.
A primaldual Laplacian gradient flow dynamics for distributed resource allocation problems.
In Proceedings of the 2018 American Control Conference,
Milwaukee, WI,
pages 53165320,
2018.
Keyword(s): Primaldual gradient flow dynamics,
Proximal augmented Lagrangian,
Distributed resource allocation,
Economic dispatch.
[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]

N. K. Dhingra,
S. Z. Khong,
and M. R. Jovanovic.
A second order primaldual algorithm for nonsmooth convex composite optimization.
In Proceedings of the 56th IEEE Conference on Decision and Control,
Melbourne, Australia,
pages 28682873,
2017.
Keyword(s): Augmented Lagrangian,
Method of multipliers,
Nonsmooth optimization,
Proximal methods,
Regularization,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification.
[bibtexentry]

A. Zare,
N. K. Dhingra,
M. R. Jovanovic,
and T. T. Georgiou.
Structured covariance completion via proximal algorithms.
In Proceedings of the 56th IEEE Conference on Decision and Control,
Melbourne, Australia,
pages 37753780,
2017.
Keyword(s): Augmented Lagrangian,
Convex optimization,
Lowrank perturbation,
Matrix completion problem,
Method of multipliers,
Nonsmooth optimization,
Proximal methods,
Regularization,
Sparsitypromoting optimal control,
Structured covariances.
[bibtexentry]

N. K. Dhingra and M. R. Jovanovic.
A method of multipliers algorithm for sparsitypromoting optimal control.
In Proceedings of the 2016 American Control Conference,
Boston, MA,
pages 19421947,
2016.
Note: (Invited paper).
Keyword(s): Augmented Lagrangian,
Method of multipliers,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control.
[bibtexentry]
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