Back to MJ's Publications
Publications about 'Proximal algorithms'


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,
2022.
Note: Doi:10.1109/TAC.2021.3115449; also arXiv:1709.01610.
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,
M. Colombino,
and M. R. Jovanovic.
Structured decentralized control of positive systems with applications to combination drug therapy and leader selection in directed networks.
IEEE Trans. Control Netw. Syst.,
6(1):352362,
March 2019.
Keyword(s): Combination drug therapy,
Convex optimization,
Directed Networks,
Leader selection,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design.
[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]

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,
2022.
Note: To appear.
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,
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]

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,
2022.
Note: Submitted.
Keyword(s): Gradient flow dynamics,
Lyapunov functions,
Proximal algorithms,
Primaldual gradient flow dynamics,
Primaldual methods,
Proximal augmented Lagrangian,
Operator splitting.
[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]

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]

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]

A. Zare and M. R. Jovanovic.
Optimal sensor selection via proximal optimization algorithms.
In Proceedings of the 57th IEEE Conference on Decision and Control,
Miami, FL,
pages 65146519,
2018.
Keyword(s): Convex optimization,
Proximal algorithms,
Sensor selection,
Semidefinite programming,
Sparsitypromoting estimation and control,
QuasiNewton methods.
[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]

M. Colombino,
N. K. Dhingra,
M. R. Jovanovic,
A. Rantzer,
and R. S. Smith.
On the optimal control problem for a class of monotone bilinear systems.
In Proceedings of the 22nd International Symposium on Mathematical Theory of Network and Systems,
Minneapolis, MN,
pages 411413,
2016.
Note: (Invited paper).
Keyword(s): Convex optimization,
Networks,
Monotone systems,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design.
[bibtexentry]

M. Colombino,
N.K. Dhingra,
M. R. Jovanovic,
and R. S. Smith.
Convex reformulation of a robust optimal control problem for a class of positive systems.
In Proceedings of the 55th IEEE Conference on Decision and Control,
Las Vegas, NV,
pages 52635268,
2016.
Note: (Invited paper).
Keyword(s): Combination drug therapy,
Convex optimization,
Networks,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design,
Robust Control.
[bibtexentry]

N. K. Dhingra,
M. Colombino,
and M. R. Jovanovic.
On the convexity of a class of structured optimal control problems for positive systems.
In Proceedings of the 2016 European Control Conference,
Aalborg, Denmark,
pages 825830,
2016.
Keyword(s): Combination drug therapy,
Convex optimization,
Leader selection,
Networks,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design.
[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]

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]
Back to MJ's Publications
Disclaimer:
This material is presented to ensure timely dissemination of
scholarly and technical work. Copyright and all rights therein
are retained by authors or by other copyright holders.
All person copying this information are expected to adhere to
the terms and constraints invoked by each author's copyright.
In most cases, these works may not be reposted
without the explicit permission of the copyright holder.
Last modified: Tue May 3 09:45:45 2022
Author: mihailo.
This document was translated from BibT_{E}X by
bibtex2html