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Publications about 'Gradient descent'


S. Samuelson.
Performance tradeoffs of accelerated firstorder optimization algorithms.
PhD thesis,
University of Southern California,
2024.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Gradient descent,
Gradientflow dynamics,
Heavyball method,
Nesterov's accelerated method,
Nonnormal dynamics,
Noise amplification,
Optimization,
Transient growth.
[bibtexentry]

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]

H. Mohammadi,
M. Razaviyayn,
and M. R. Jovanovic.
Tradeoffs between convergence rate and noise amplification for momentumbased accelerated optimization algorithms.
IEEE Trans. Automat. Control,
2024.
Note: Doi:10.1109/TAC.2024.3453656.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Gradient descent,
Fundamental limitations,
Heavyball method,
Nesterov's accelerated method,
Nonnormal dynamics,
Noise amplification,
Secondorder moments.
[bibtexentry]

W. Wu,
J. Chen,
M. R. Jovanovic,
and T. T. Georgiou.
Tannenbaum's gainmargin optimization meets Polyak's heavyball algorithm.
IEEE Trans. Automat. Control,
2024.
Note: Submitted; also arXiv:2409.19882.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Gradient descent,
Fundamental limitations,
Heavyball method,
Integral quadratic constraints,
Nesterov's accelerated method,
NevanlinnaPick interpolation,
Optimization,
Optimal control,
Robust control.
[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,
H. Mohammadi,
and M. R. Jovanovic.
Computing stabilizing feedback gains via a modelfree policy gradient method.
IEEE Control Syst. Lett.,
7:407412,
July 2023.
Keyword(s): Datadriven control,
Gradient descent,
Linear quadratic regulator,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
Random search method,
Reinforcement learning,
Sample complexity.
[bibtexentry]

H. Mohammadi,
A. Zare,
M. Soltanolkotabi,
and M. R. Jovanovic.
Convergence and sample complexity of gradient methods for the modelfree linearquadratic regulator problem.
IEEE Trans. Automat. Control,
67(5):24352450,
May 2022.
Keyword(s): Datadriven control,
Gradient descent,
Gradientflow dynamics,
Linear quadratic regulator,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
PolyakLojasiewicz inequality,
Random search method,
Reinforcement learning,
Sample complexity.
[bibtexentry]

H. Mohammadi,
M. Soltanolkotabi,
and M. R. Jovanovic.
On the linear convergence of random search for discretetime LQR.
IEEE Control Syst. Lett.,
5(3):989994,
July 2021.
Keyword(s): Datadriven control,
Gradient descent,
Linear quadratic regulator,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
Random search method,
Reinforcement learning,
Sample complexity.
[bibtexentry]

W. Wu,
J. Chen,
M. R. Jovanovic,
and T. T. Georgiou.
Frequencydomain synthesis of implicit algorithms.
In Proceedings of the 2025 American Control Conference,
Denver, CO,
2025.
Note: Submitted.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Gradient descent,
Heavyball method,
Integral quadratic constraints,
Nesterov's accelerated method,
Optimization,
Optimal control.
[bibtexentry]

I. K. Ozaslan and M. R. Jovanovic.
From exponential to finite/fixedtime stability: applications to optimization.
In Proceedings of the 63rd IEEE Conference on Decision and Control,
Milano, Italy,
2024.
Note: To appear.
Keyword(s): Exponential stability,
Finitetime stability,
Fixedtime stability,
Normalized gradient descent,
Gradient flow dynamics,
Primaldual methods.
[bibtexentry]

H. Mohammadi,
M. Razaviyayn,
and M. R. Jovanovic.
Noise amplification of momentumbased optimization algorithms.
In Proceedings of the 2023 American Control Conference,
San Diego, CA,
pages 849854,
2023.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Gradient descent,
Heavyball method,
Nesterov's accelerated method,
Noise amplification,
Nonnormal dynamics,
Twostep momentum algorithm.
[bibtexentry]

H. Mohammadi,
M. Soltanolkotabi,
and M. R. Jovanovic.
On the lack of gradient domination for linear quadratic Gaussian problems with incomplete state information.
In Proceedings of the 60th IEEE Conference on Decision and Control,
Austin, TX,
pages 11201124,
2021.
Keyword(s): Datadriven control,
Gradient descent,
Gradientflow dynamics,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
PolyakLojasiewicz inequality,
Random search method,
Reinforcement learning,
Sample complexity.
[bibtexentry]

H. Mohammadi,
M. Soltanolkotabi,
and M. R. Jovanovic.
Learning the modelfree linear quadratic regulator via random search.
In Proceedings of Machine Learning Research, 2nd Annual Conference on Learning for Dynamics and Control,
volume 120,
Berkeley, CA,
pages 19,
2020.
Keyword(s): Datadriven control,
Gradient descent,
Gradientflow dynamics,
Linear quadratic regulator,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
PolyakLojasiewicz inequality,
Random search method,
Reinforcement learning,
Sample complexity.
[bibtexentry]

H. Mohammadi,
M. Soltanolkotabi,
and M. R. Jovanovic.
Random search for learning the linear quadratic regulator.
In Proceedings of the 2020 American Control Conference,
Denver, CO,
pages 47984803,
2020.
Keyword(s): Datadriven control,
Gradient descent,
Gradientflow dynamics,
Linear quadratic regulator,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
PolyakLojasiewicz inequality,
Random search method,
Reinforcement learning,
Sample complexity.
[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]

S. Samuelson,
H. Mohammadi,
and M. R. Jovanovic.
Transient growth of accelerated firstorder methods.
In Proceedings of the 2020 American Control Conference,
Denver, CO,
pages 28582863,
2020.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convex optimization,
Gradient descent,
Transient growth.
[bibtexentry]

H. Mohammadi,
A. Zare,
M. Soltanolkotabi,
and M. R. Jovanovic.
Global exponential convergence of gradient methods over the nonconvex landscape of the linear quadratic regulator.
In Proceedings of the 58th IEEE Conference on Decision and Control,
Nice, France,
pages 74747479,
2019.
Keyword(s): Datadriven control,
Global exponential stability,
Gradient descent,
Gradientflow dynamics,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
Reinforcement learning.
[bibtexentry]

H. Mohammadi,
M. Soltanolkotabi,
and M. R. Jovanovic.
Modelfree linear quadratic regulator.
In K. G. Vamvoudakis,
Y. Wan,
F. Lewis,
and D. Cansever, editors, Handbook of Reinforcement Learning and Control.
Springer International Publishing,
2021.
Note: Doi:10.1007/9783030609900.
Keyword(s): Datadriven control,
Gradient descent,
Gradientflow dynamics,
Linear quadratic regulator,
Modelfree control,
Nonconvex optimization,
Optimization,
Optimal control,
PolyakLojasiewicz inequality,
Random search method,
Reinforcement learning,
Sample complexity.
[bibtexentry]
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Last modified: Sat Oct 5 22:00:41 2024
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