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Publications about 'Noise amplification'
Theses
  1. H. Mohammadi. Robustness of gradient methods for data-driven decision making. PhD thesis, University of Southern California, 2022. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convergence rate, Convex optimization, Data-driven control, Gradient descent, Gradient-flow dynamics, Heavy-ball method, Integral quadratic constraints, Linear quadratic regulator, Model-free control, Nesterov's accelerated method, Nonconvex optimization, Nonnormal dynamics, Noise amplification, Optimization, Optimal control, Polyak-Lojasiewicz inequality, Random search method, Reinforcement learning, Sample complexity, Second-order moments, Transient growth. [bibtex-entry]


Journal articles
  1. L. Ballotta, M. R. Jovanovic, and L. Schenato. Can decentralized control outperform centralized? The role of communication latency. IEEE Trans. Control Netw. Syst., 10(3):1629-1640, September 2023. Keyword(s): Controller architecture, Fundamental limitations, Networks, Networks of dynamical systems, Noise amplification, Performance bounds, Topology design. [bibtex-entry]


  2. H. Mohammadi, M. Razaviyayn, and M. R. Jovanovic. Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms. IEEE Trans. Automat. Control, 2022. Note: Submitted; also arXiv:2209.11920. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convergence rate, Convex optimization, Gradient descent, Heavy-ball method, Nesterov's accelerated method, Nonnormal dynamics, Noise amplification, Second-order moments. [bibtex-entry]


  3. H. Mohammadi, M. Razaviyayn, and M. R. Jovanovic. Robustness of accelerated first-order algorithms for strongly convex optimization problems. IEEE Trans. Automat. Control, 66(6):2480-2495, June 2021. Keyword(s): Accelerated first-order algorithms, Consensus networks, Control for optimization, Convex optimization, Integral quadratic constraints, Linear matrix inequalities, Noise amplification, Second-order moments, Semidefinite programming. [bibtex-entry]


Conference articles
  1. S. Samuelson and M. R. Jovanovic. Tradeoffs between convergence speed and noise amplification in first-order optimization: the role of averaging. In Proceedings of the 2024 American Control Conference, Toronto, Canada, 2024. Note: To appear. Keyword(s): Accelerated first-order algorithms, Averaging, Control for optimization, Convergence rate, Convex optimization, Gradient flow dynamics, Noise amplification, Nonnormal dynamics, Two-step momentum algorithm. [bibtex-entry]


  2. A. Dwivedi and M. R. Jovanovic. Noise amplification in hypersonic blunt body flows. In Proceedings of the 2023 AIAA Aviation and Aeronautics Forum, San Diego, CA, pages 3709 (12 pages), 2023. Keyword(s): Compressible flows, Input-output analysis, Energy amplification, Flow modeling and control, High-speed compressible boundary layers, Hypersonic flows, Transition to turbulence. [bibtex-entry]


  3. H. Mohammadi, M. Razaviyayn, and M. R. Jovanovic. Noise amplification of momentum-based optimization algorithms. In Proceedings of the 2023 American Control Conference, San Diego, CA, pages 849-854, 2023. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convergence rate, Convex optimization, Gradient descent, Heavy-ball method, Nesterov's accelerated method, Noise amplification, Nonnormal dynamics, Two-step momentum algorithm. [bibtex-entry]


  4. S. Samuelson, H. Mohammadi, and M. R. Jovanovic. Performance of noisy higher-order accelerated gradient flow dynamics for strongly convex quadratic optimization problems. In Proceedings of the 2023 American Control Conference, San Diego, CA, pages 3839-3844, 2023. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convergence rate, Convex optimization, Gradient flow dynamics, Noise amplification, Nonnormal dynamics, Two-step momentum algorithm. [bibtex-entry]


  5. S. Samuelson, H. Mohammadi, and M. R. Jovanovic. Performance of noisy three-step accelerated first-order optimization algorithms for strongly convex quadratic problems. In Proceedings of the 62nd IEEE Conference on Decision and Control, Singapore, pages 1300-1305, 2023. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convergence rate, Convex optimization, Gradient flow dynamics, Noise amplification, Nonnormal dynamics, Three-step momentum algorithm. [bibtex-entry]


  6. L. Ballotta, M. R. Jovanovic, and L. Schenato. Can decentralized control outperform centralized? The role of communication latency. In Proceedings of the 2022 IFAC Conference on Networked Systems, Zurich, Switzerland, 2022. Keyword(s): Controller architecture, Fundamental limitations, Networks, Networks of dynamical systems, Noise amplification, Performance bounds, Topology design. [bibtex-entry]


  7. H. Mohammadi and M. R. Jovanovic. On the noise amplification of primal-dual gradient flow dynamics based on proximal augmented Lagrangian. In Proceedings of the 2022 American Control Conference, Atlanta, GA, pages 926-931, 2022. Keyword(s): Control for optimization, Convex Optimization, Integral quadratic constraints, Linear matrix inequalities, Noise amplification, Non-smooth optimization, Proximal algorithms, Primal-dual gradient flow dynamics, Primal-dual methods, Proximal augmented Lagrangian, Second-order moments, Semidefinite programming. [bibtex-entry]


  8. L. Ballotta, M. R. Jovanovic, and L. Schenato. Optimal network topology of multi-agent systems subject to computation and communication latency. In Proceedings of the 29th Mediterranean Conference on Control and Automation, Bari, Italy, pages 249-254, 2021. Keyword(s): Controller architecture, Fundamental limitations, Networks, Networks of dynamical systems, Noise amplification, Performance bounds, Topology design. [bibtex-entry]


  9. 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 3426-3431, 2019. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convex optimization, Integral quadratic constraints, Linear matrix inequalities, Noise amplification, Second-order moments, Semidefinite programming. [bibtex-entry]



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Last modified: Tue Jan 23 11:32:51 2024
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