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Publications about 'Augmented Lagrangian'
Theses
  1. S. Hassan-Moghaddam. Analysis, design, and optimization of large-scale networks of dynamical systems. PhD thesis, University of Southern California, 2019. Keyword(s): Consensus, Control for optimization, Convex Optimization, Distributed control, Forward-backward envelope, Douglas-Rachford splitting, Global exponential stability, Integral quadratic constraints, Networks of dynamical systems, Non-smooth optimization, Polyak-Lojasiewicz inequality, Proximal algorithms, Primal-dual methods, Proximal augmented Lagrangian, Regularization for design, Sparse graphs, Sparsity-promoting optimal control, Structured optimal control, Structure identification, Topology design. [bibtex-entry]


  2. N. K. Dhingra. Optimization and control of large-scale networked systems. PhD thesis, University of Minnesota, 2017. Keyword(s): Augmented Lagrangian, Combination drug therapy, Convex optimization, Directed networks, Leader selection, Method of multipliers, Non-smooth optimization, Optimization, Proximal algorithms, Proximal augmented Lagrangian, Regularization, Second order primal-dual method, Sparsity-promoting optimal control, Structured optimal control, Structure identification. [bibtex-entry]


Journal articles
  1. I. K. Ozaslan, P. Patrinos, and M. R. Jovanovic. Stability of primal-dual gradient flow dynamics for multi-block convex optimization problems. IEEE Trans. Automat. Control, 2024. Note: Submitted; also arXiv:2408.15969. Keyword(s): Augmented Lagrangian, Exponential convergence, Distributed optimization, Global exponential stability, Gradient flow dynamics, Method of multipliers, Non-smooth optimization, Operator splitting, Primal-dual gradient flow dynamics, Proximal algorithms, Proximal augmented Lagrangian, Regularization for design. [bibtex-entry]


  2. N. K. Dhingra, S. Z. Khong, and M. R. Jovanovic. A second order primal-dual method for nonsmooth convex composite optimization. IEEE Trans. Automat. Control, 67(8):4061-4076, August 2022. Keyword(s): Augmented Lagrangian, Exponential convergence, Global exponential stability, Method of multipliers, Non-smooth optimization, Proximal algorithms, Proximal augmented Lagrangian, Regularization for design, Second order primal-dual method, Sparsity-promoting optimal control, Structured optimal control, Structure identification. [bibtex-entry]


  3. S. Hassan-Moghaddam and M. R. Jovanovic. Proximal gradient flow and Douglas-Rachford splitting dynamics: global exponential stability via integral quadratic constraints. Automatica, 123:109311, January 2021. Keyword(s): Control for optimization, Convex Optimization, Forward-backward envelope, Douglas-Rachford splitting, Global exponential stability, Integral quadratic constraints, Non-smooth optimization, Polyak-Lojasiewicz inequality, Proximal algorithms, Primal-dual methods, Proximal augmented Lagrangian. [bibtex-entry]


  4. A. Zare, H. Mohammadi, N. K. Dhingra, T. T. Georgiou, and M. R. Jovanovic. Proximal algorithms for large-scale statistical modeling and sensor/actuator selection. IEEE Trans. Automat. Control, 65(8):3441-3456, August 2020. Keyword(s): Actuator selection, Augmented Lagrangian, Convex optimization, Low-rank perturbation, Matrix completion problem, Method of multipliers, Non-smooth optimization, Proximal algorithms, Regularization for design, Sensor selection, Sparsity-promoting optimal control, Structured covariances. [bibtex-entry]


  5. 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):2861-2868, July 2019. Keyword(s): Augmented Lagrangian, Control for optimization, Exponential convergence, Global exponential stability, Method of multipliers, Non-smooth optimization, Primal-dual gradient flow dynamics, Proximal algorithms, Proximal augmented Lagrangian, Regularization for design, Sparsity-promoting optimal control, Structured optimal control, Structure identification. [bibtex-entry]


  6. 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):2923-2929, December 2011. Keyword(s): Architectural issues in distributed control design, Distributed control, Optimal localized control. [bibtex-entry]


Conference articles
  1. 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]


  2. I. K. Ozaslan, S. Hassan-Moghaddam, and M. R. Jovanovic. On the asymptotic stability of proximal algorithms for convex optimization problems with multiple non-smooth regularizers. In Proceedings of the 2022 American Control Conference, Atlanta, GA, pages 132-137, 2022. Keyword(s): Control for optimization, Convex Optimization, Douglas-Rachford splitting, Global asymptotic stability, Lyapunov-based analysis, Non-smooth optimization, Proximal algorithms, Primal-dual gradient flow dynamics, Primal-dual methods, Proximal augmented Lagrangian. [bibtex-entry]


  3. I. K. Ozaslan and M. R. Jovanovic. Exponential convergence of primal-dual dynamics for multi-block problems under local error bound condition. In Proceedings of the 61th IEEE Conference on Decision and Control, Cancun, Mexico, pages 7579-7584, 2022. Keyword(s): Gradient flow dynamics, Lyapunov functions, Proximal algorithms, Primal-dual gradient flow dynamics, Primal-dual methods, Proximal augmented Lagrangian, Operator splitting. [bibtex-entry]


  4. D. Ding and M. R. Jovanovic. Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian: A Lyapunov-based approach. In Proceedings of the 59th IEEE Conference on Decision and Control, Jeju Island, Republic of Korea, pages 4836-4841, 2020. Keyword(s): Augmented Lagrangian, Control for optimization, Convex optimization, Global exponential stability, Lyapunov-based approach, Non-smooth optimization, Primal-dual gradient flow dynamics, Primal-dual methods, Proximal augmented Lagrangian. [bibtex-entry]


  5. S. Hassan-Moghaddam and M. R. Jovanovic. Global exponential stability of the Douglas-Rachford splitting dynamics. In Preprints of the 21st IFAC World Congress, Berlin, Germany, pages 7350-7354, 2020. Keyword(s): Control for optimization, Convex Optimization, Forward-backward envelope, Douglas-Rachford splitting, Global exponential stability, Integral quadratic constraints, Non-smooth optimization, Polyak-Lojasiewicz inequality, Proximal algorithms, Primal-dual methods, Proximal augmented Lagrangian. [bibtex-entry]


  6. D. Ding and M. R. Jovanovic. Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian. In Proceedings of the 2019 American Control Conference, Philadelphia, PA, pages 3414-3419, 2019. Keyword(s): Convex optimization, Global exponential stability, Non-smooth optimization, Primal-dual gradient flow dynamics, Proximal augmented Lagrangian method. [bibtex-entry]


  7. D. Ding, B. Hu, N. K. Dhingra, and M. R. Jovanovic. An exponentially convergent primal-dual algorithm for nonsmooth composite minimization. In Proceedings of the 57th IEEE Conference on Decision and Control, Miami, FL, pages 4927-4932, 2018. Keyword(s): Control for optimization, Convex optimization, Euler discretization, Exponential convergence, Global exponential stability, Integral quadratic constraints, Proximal augmented Lagrangian, Non-smooth optimization, Primal-dual gradient flow dynamics, Proximal algorithms, Regularization. [bibtex-entry]


  8. D. Ding and M. R. Jovanovic. A primal-dual Laplacian gradient flow dynamics for distributed resource allocation problems. In Proceedings of the 2018 American Control Conference, Milwaukee, WI, pages 5316-5320, 2018. Keyword(s): Primal-dual gradient flow dynamics, Proximal augmented Lagrangian, Distributed resource allocation, Economic dispatch. [bibtex-entry]


  9. S. Hassan-Moghaddam and M. R. Jovanovic. Distributed proximal augmented Lagrangian method for nonsmooth composite optimization. In Proceedings of the 2018 American Control Conference, Milwaukee, WI, pages 2047-2052, 2018. Keyword(s): Consensus, Distributed Optimization, Non-smooth optimization, Primal-dual gradient flow dynamics, Proximal augmented Lagrangian. [bibtex-entry]


  10. S. Hassan-Moghaddam 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 4246-4251, 2018. Note: (Invited paper). Keyword(s): Control for optimization, Distributed optimization, Forward-backward envelope, Exponential convergence, Global exponential stability, Gradient flow dynamics, Large-scale systems, Non-smooth optimization, Primal-dual method, Proximal algorithms, Proximal augmented Lagrangian. [bibtex-entry]


  11. N. K. Dhingra, S. Z. Khong, and M. R. Jovanovic. A second order primal-dual algorithm for non-smooth convex composite optimization. In Proceedings of the 56th IEEE Conference on Decision and Control, Melbourne, Australia, pages 2868-2873, 2017. Keyword(s): Augmented Lagrangian, Method of multipliers, Non-smooth optimization, Proximal methods, Regularization, Sparsity-promoting optimal control, Structured optimal control, Structure identification. [bibtex-entry]


  12. 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 3775-3780, 2017. Keyword(s): Augmented Lagrangian, Convex optimization, Low-rank perturbation, Matrix completion problem, Method of multipliers, Non-smooth optimization, Proximal methods, Regularization, Sparsity-promoting optimal control, Structured covariances. [bibtex-entry]


  13. N. K. Dhingra and M. R. Jovanovic. A method of multipliers algorithm for sparsity-promoting optimal control. In Proceedings of the 2016 American Control Conference, Boston, MA, pages 1942-1947, 2016. Note: (Invited paper). Keyword(s): Augmented Lagrangian, Method of multipliers, Proximal algorithms, Optimization, Sparsity-promoting optimal control. [bibtex-entry]



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Last modified: Sat Oct 5 22:00:41 2024
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