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Publications about 'Proximal algorithms'
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 and M. R. Jovanovic. Accelerated forward-backward and Douglas-Rachford splitting dynamics. Automatica, 2023. Note: Submitted. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convex Optimization, Forward-backward envelope, Douglas-Rachford splitting, Global exponential stability, Integral quadratic constraints, Nesterov's accelerated method, Non-smooth optimization, Proximal algorithms. [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, 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):352-362, March 2019. Keyword(s): Combination drug therapy, Convex optimization, Directed Networks, Leader selection, Positive systems, Proximal algorithms, Optimization, Sparsity-promoting optimal control, Structured design. [bibtex-entry]


  6. 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]


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. 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]


  5. S. Hassan-Moghaddam, M. R. Jovanovic, and S. Meyn. Data-driven proximal algorithms for the design of structured optimal feedback gains. In Proceedings of the 2019 American Control Conference, Philadelphia, PA, pages 5846-5850, 2019. Keyword(s): Data-driven feedback design, Large-scale systems, Non-smooth optimization, Proximal algorithms, Reinforcement learning, Sparsity-promoting optimal control, Structured optimal control. [bibtex-entry]


  6. 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]


  7. 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]


  8. 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 6514-6519, 2018. Keyword(s): Convex optimization, Proximal algorithms, Sensor selection, Semidefinite programming, Sparsity-promoting estimation and control, Quasi-Newton methods. [bibtex-entry]


  9. 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]


  10. 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 411-413, 2016. Note: (Invited paper). Keyword(s): Convex optimization, Networks, Monotone systems, Positive systems, Proximal algorithms, Optimization, Sparsity-promoting optimal control, Structured design. [bibtex-entry]


  11. 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 5263-5268, 2016. Note: (Invited paper). Keyword(s): Combination drug therapy, Convex optimization, Networks, Positive systems, Proximal algorithms, Optimization, Sparsity-promoting optimal control, Structured design, Robust Control. [bibtex-entry]


  12. 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 825-830, 2016. Keyword(s): Combination drug therapy, Convex optimization, Leader selection, Networks, Positive systems, Proximal algorithms, Optimization, Sparsity-promoting optimal control, Structured design. [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]


  14. S. Hassan-Moghaddam 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 986-991, 2016. Keyword(s): Convex optimization, Coordinate descent algorithm, Networks, Proximal algorithms. [bibtex-entry]



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