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Publications about 'Integral quadratic constraints'


H. Mohammadi.
Robustness of gradient methods for datadriven decision making.
PhD thesis,
University of Southern California,
2022.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Datadriven control,
Gradient descent,
Gradientflow dynamics,
Heavyball method,
Integral quadratic constraints,
Linear quadratic regulator,
Modelfree control,
Nesterov's accelerated method,
Nonconvex optimization,
Nonnormal dynamics,
Noise amplification,
Optimization,
Optimal control,
PolyakLojasiewicz inequality,
Random search method,
Reinforcement learning,
Sample complexity,
Secondorder moments,
Transient growth.
[bibtexentry]

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]

H. Mohammadi,
S. Samuelson,
and M. R. Jovanovic.
Transient growth of accelerated optimization algorithms.
IEEE Trans. Automat. Control,
68(3):18231830,
March 2023.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convex optimization,
Gradient descent,
Heavyball method,
Integral quadratic constraints,
Nesterov's accelerated method,
Nonnormal dynamics,
Transient growth.
[bibtexentry]

I. K. Ozaslan and M. R. Jovanovic.
Accelerated forwardbackward and DouglasRachford splitting dynamics.
Automatica,
2023.
Note: Submitted.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convex Optimization,
Forwardbackward envelope,
DouglasRachford splitting,
Global exponential stability,
Integral quadratic constraints,
Nesterov's accelerated method,
Nonsmooth optimization,
Proximal algorithms.
[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]

H. Mohammadi,
M. Razaviyayn,
and M. R. Jovanovic.
Robustness of accelerated firstorder algorithms for strongly convex optimization problems.
IEEE Trans. Automat. Control,
66(6):24802495,
June 2021.
Keyword(s): Accelerated firstorder algorithms,
Consensus networks,
Control for optimization,
Convex optimization,
Integral quadratic constraints,
Linear matrix inequalities,
Noise amplification,
Secondorder moments,
Semidefinite programming.
[bibtexentry]

I. K. Ozaslan and M. R. Jovanovic.
Tight lower bounds on the convergence rate of primaldual dynamics for equality constrained convex problems.
In Proceedings of the 62nd IEEE Conference on Decision and Control,
Singapore,
pages 73127317,
2023.
Keyword(s): Gradient flow dynamics,
Exponential stability,
Integral quadratic constraints,
Primaldual gradient flow dynamics,
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]

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. Samuelson,
H. Mohammadi,
and M. R. Jovanovic.
On the transient growth of Nesterov's accelerated method for strongly convex optimization problems.
In Proceedings of the 59th IEEE Conference on Decision and Control,
Jeju Island, Republic of Korea,
pages 59115916,
2020.
Note: (Invited paper).
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convex optimization,
Gradient descent,
Integral quadratic constraints,
Nesterov's accelerated method,
Nonnormal dynamics,
Transient growth.
[bibtexentry]

H. Mohammadi,
M. Razaviyayn,
and M. R. Jovanovic.
Performance of noisy Nesterov's accelerated method for strongly convex optimization problems.
In Proceedings of the 2019 American Control Conference,
Philadelphia, PA,
pages 34263431,
2019.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convex optimization,
Integral quadratic constraints,
Linear matrix inequalities,
Noise amplification,
Secondorder moments,
Semidefinite programming.
[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]
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Last modified: Tue Jan 23 11:32:51 2024
Author: mihailo.
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