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Publications about 'Convex optimization'
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]


  3. A. Zare. Low-complexity stochastic modeling of wall-bounded shear flows. PhD thesis, University of Minnesota, 2016. Keyword(s): Alternating minimization algorithm, Colored noise, Convex optimization, Disturbance dynamics, Flow modeling and control, Low-complexity modeling, Low-rank approximation, Matrix completion problem, Nuclear norm regularization, Structured covariances, Turbulence modeling. [bibtex-entry]


  4. F. Lin. Structure identification and optimal design of large-scale networks of dynamical systems. PhD thesis, University of Minnesota, 2012. Keyword(s): Alternating direction method of multipliers, Architectural issues in distributed control design, Consensus networks, Control of vehicular formations, Convex Optimization, Leader selection, Sparsity-promoting optimal control. [bibtex-entry]


Journal articles
  1. 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]


  2. M. R. Jovanovic. From bypass transition to flow control and data-driven turbulence modeling: An input-output viewpoint. Annu. Rev. Fluid Mech., 53(1):311-345, January 2021. Keyword(s): Colored noise, Convex optimization, Drag reduction, Energy amplification, Flow modeling and control, Input-output analysis, Low-complexity modeling, Low-rank approximation, Matrix completion problems, Navier-Stokes equations, Nuclear norm regularization, Simulation-free design, Structured covariances, Transition to turbulence, Turbulence modeling. [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]


  4. H. Mohammadi, S. Samuelson, and M. R. Jovanovic. Transient growth of accelerated first-order methods for strongly convex optimization problems. IEEE Trans. Automat. Control, 2021. Note: Submitted; also arXiv:2103.08017. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convex optimization, Gradient descent, Heavy-ball method, Integral quadratic constraints, Nesterov's accelerated method, Nonnormal dynamics, Transient growth. [bibtex-entry]


  5. D. Ding, X. Wei, Z. Yang, Z. Wang, and M. R. Jovanovic. Fast multi-agent temporal-difference learning via homotopy stochastic primal-dual optimization. IEEE Trans. Automat. Control, 2020. Note: Submitted; also arXiv:1908.02805. Keyword(s): Convex optimization, Distributed temporal-difference learning, Multi-agent systems, Primal-dual algorithms, Reinforcement learning, Stochastic optimization. [bibtex-entry]


  6. A. Zare, T. T. Georgiou, and M. R. Jovanovic. Stochastic dynamical modeling of turbulent flows. Annu. Rev. Control Robot. Auton. Syst., 3:195-219, May 2020. Keyword(s): Colored noise, Convex optimization, Disturbance dynamics, Flow modeling and control, Low-complexity modeling, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances, Turbulence modeling. [bibtex-entry]


  7. 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]


  8. 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]


  9. S. Hassan-Moghaddam and M. R. Jovanovic. Topology design for stochastically-forced consensus networks. IEEE Trans. Control Netw. Syst., 5(3):1075-1086, September 2018. Keyword(s): Consensus, Convex optimization, Distributed control, Interior point method, Proximal gradient method, Proximal Newton method, Sparse graphs, Topology design. [bibtex-entry]


  10. A. Zare, Y. Chen, M. R. Jovanovic, and T. T. Georgiou. Low-complexity modeling of partially available second-order statistics: theory and an efficient matrix completion algorithm. IEEE Trans. Automat. Control, 62(3):1368-1383, March 2017. Keyword(s): Alternating minimization algorithm, Convex optimization, Disturbance dynamics, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  11. A. Zare, M. R. Jovanovic, and T. T. Georgiou. Colour of turbulence. J. Fluid Mech., 812:636-680, February 2017. Keyword(s): Colored noise, Convex optimization, Disturbance dynamics, Flow modeling and control, Low-complexity modeling, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances, Turbulence modeling. [bibtex-entry]


  12. M. R. Jovanovic and N. K. Dhingra. Controller architectures: tradeoffs between performance and structure. Eur. J. Control, 30:76-91, July 2016. Keyword(s): Controller architecture, Convex optimization, Distributed control, Networks of dynamical systems, Non-smooth optimization, Performance vs. complexity, Regularization, Sparsity-promoting optimal control, Structured optimal control, Structure identification. [bibtex-entry]


  13. M. R. Jovanovic, P. J. Schmid, and J. W. Nichols. Sparsity-promoting dynamic mode decomposition. Phys. Fluids, 26(2):024103 (22 pages), February 2014. Keyword(s): Dynamic Mode Decomposition, Flow modeling and control, Convex optimization, Sparsity. [bibtex-entry]


  14. F. Lin, M. Fardad, and M. R. Jovanovic. Algorithms for leader selection in stochastically forced consensus networks. IEEE Trans. Automat. Control, 59(7):1789-1802, July 2014. Keyword(s): Alternating direction method of multipliers, Consensus networks, Convex optimization, Greedy algorithm, Leader selection, Performance bounds, Sparsity. [bibtex-entry]


  15. R. Moarref, M. R. Jovanovic, J. A. Tropp, A. S. Sharma, and B. J. McKeon. A low-order decomposition of turbulent channel flow via resolvent analysis and convex optimization. Phys. Fluids, 26(5):051701 (7 pages), May 2014. Keyword(s): Flow modeling and control, Convex optimization, Low-rank approximation. [bibtex-entry]


Conference articles
  1. D. Ding, X. Wei, Z. Yang, Z. Wang, and M. R. Jovanovic. Provably efficient safe exploration via primal-dual policy optimization. In 24th International Conference on Artificial Intelligence and Statistics, volume 130, Virtual, pages 3304-3312, 2021. Keyword(s): Safe reinforcement learning, Constrained Markov decision processes, Safe exploration, Proximal policy optimization, Non-convex optimization, Online mirror descent, Primal-dual method. [bibtex-entry]


  2. 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]


  3. S. Hassan-Moghaddam and M. R. Jovanovic. Global exponential stability of the Douglas-Rachford splitting dynamics. In Preprints of the 21th IFAC World Congress, Berlin, Germany, 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]


  4. 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 5911-5916, 2020. Note: (Invited paper). Keyword(s): Accelerated first-order algorithms, Control for optimization, Convex optimization, Gradient descent, Integral quadratic constraints, Nesterov's accelerated method, Nonnormal dynamics, Transient growth. [bibtex-entry]


  5. S. Samuelson, H. Mohammadi, and M. R. Jovanovic. Transient growth of accelerated first-order methods. In Proceedings of the 2020 American Control Conference, Denver, CO, pages 2858-2863, 2020. Keyword(s): Accelerated first-order algorithms, Control for optimization, Convex optimization, Gradient descent, Transient growth. [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, X. Wei, Z. Yang, Z. Wang, and M. R. Jovanovic. Fast multi-agent temporal-difference learning via homotopy stochastic primal-dual method. In Optimization Foundations for Reinforcement Learning Workshop, 33rd Conference on Neural Information Processing Systems, Vancouver, Canada, 2019. Keyword(s): Convex optimization, Distributed temporal-difference learning, Multi-agent systems, Primal-dual algorithms, Reinforcement learning, Stochastic optimization. [bibtex-entry]


  8. 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]


  9. 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]


  10. S. Hassan-Moghaddam and M. R. Jovanovic. Topology identification via growing a Chow-Liu tree network. In Proceedings of the 57th IEEE Conference on Decision and Control, Miami, FL, pages 5421-5426, 2018. Keyword(s): Chow-Liu tree, Consensus, Convex optimization, Graphical LASSO, Sparse graphs, Topology identification, Maximum likelihood, Sparse inverse covariance estimation. [bibtex-entry]


  11. 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]


  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. J. Annoni, P. Seiler, and M. R. Jovanovic. Sparsity-promoting dynamic mode decomposition for systems with inputs. In Proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, NV, pages 6506-6511, 2016. Note: (Invited paper). Keyword(s): Dynamic Mode Decomposition, Flow modeling and control, Convex optimization, Sparsity. [bibtex-entry]


  14. 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]


  15. 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]


  16. N. K. Dhingra, M. Colombino, and M. R. Jovanovic. Leader selection in directed networks. In Proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, NV, pages 2715-2720, 2016. Note: (Invited paper). Keyword(s): Consensus networks, Convex optimization, Positive systems, Leader selection. [bibtex-entry]


  17. 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]


  18. N. K. Dhingra, X. Wu, and M. R. Jovanovic. Sparsity-promoting optimal control of systems with invariances and symmetries. In Proceedings of the 10th IFAC Symposium on Nonlinear Control Systems, Monterey, CA, pages 648-653, 2016. Keyword(s): Architectural issues in distributed control design, Cardinality minimization, Convex optimization, Distributed control, Sparsity-promoting optimal control, Spatially-invariant systems, Symmetric systems. [bibtex-entry]


  19. C. Grussler, A. Zare, M. R. Jovanovic, and A. Rantzer. The use of the $r*$ heuristic in covariance completion problems. In Proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, NV, pages 1978-1983, 2016. Keyword(s): Convex optimization, $k$-support-norm, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  20. S. Hassan-Moghaddam, N. K. Dhingra, and M. R. Jovanovic. Topology identification of undirected consensus networks via sparse inverse covariance estimation. In Proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, NV, pages 4624-4629, 2016. Keyword(s): Consensus, Convex optimization, Sparse graphs, Topology identification, Maximum likelihood, Sparse inverse covariance estimation. [bibtex-entry]


  21. 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]


  22. A. Zare, Y. Chen, M. R. Jovanovic, and T. T. Georgiou. An alternating minimization algorithm for structured covariance completion problems. In Proceedings of the 22nd International Symposium on Mathematical Theory of Network and Systems, Minneapolis, MN, pages 117-119, 2016. Keyword(s): Alternating minimization algorithm, Convex optimization, Disturbance dynamics, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  23. A. Zare, M. R. Jovanovic, and T. T. Georgiou. Perturbation of system dynamics and the covariance completion problem. In Proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, NV, pages 7036-7041, 2016. Keyword(s): Convex optimization, Low-rank perturbation, Matrix completion problems, Sparsity-promoting optimal control, Structured covariances. [bibtex-entry]


  24. S. Hassan-Moghaddam and M. R. Jovanovic. An interior point method for growing connected resistive networks. In Proceedings of the 2015 American Control Conference, Chicago, IL, pages 1223-1228, 2015. Keyword(s): Consensus, Convex optimization, Distributed control, Interior point method, Sparse graphs, Topology design. [bibtex-entry]


  25. A. Zare, M. R. Jovanovic, and T. T. Georgiou. Alternating direction optimization algorithms for covariance completion problems. In Proceedings of the 2015 American Control Conference, Chicago, IL, pages 515-520, 2015. Keyword(s): Alternating direction method of multipliers, Alternating minimization algorithm, Convex optimization, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  26. N. K. Dhingra, M. R. Jovanovic, and Z. Q. Luo. An ADMM algorithm for optimal sensor and actuator selection. In Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, CA, pages 4039-4044, 2014. Note: (Invited paper). Keyword(s): Alternating direction method of multipliers, Convex optimization, Actuator selection, Sensor selection. [bibtex-entry]


  27. M. Fardad and M. R. Jovanovic. On the design of optimal structured and sparse feedback gains using semidefinite programming. In Proceedings of the 2014 American Control Conference, Portland, OR, pages 2438-2443, 2014. Keyword(s): Architectural issues in distributed control design, Cardinality minimization, Convex optimization, Distributed control, Sparsity-promoting optimal control. [bibtex-entry]


  28. A. Zare, M. R. Jovanovic, and T. T. Georgiou. Completion of partially known turbulent flow statistics. In Proceedings of the 2014 American Control Conference, Portland, OR, pages 1680-1685, 2014. Note: (Invited paper; Finalist, Best Student Paper Award). Keyword(s): Alternating direction method of multipliers, Convex optimization, Flow modeling and control, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  29. A. Zare, M. R. Jovanovic, and T. T. Georgiou. Completion of partially known turbulent flow statistics via convex optimization. In Proceedings of the 2014 Summer Program, Center for Turbulence Research, Stanford University/NASA, pages 345-354, 2014. Keyword(s): Convex optimization, Flow modeling and control, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  30. D. M. Zoltowski, N. K. Dhingra, F. Lin, and M. R. Jovanovic. Sparsity-promoting optimal control of spatially-invariant systems. In Proceedings of the 2014 American Control Conference, Portland, OR, pages 1261-1266, 2014. Keyword(s): Architectural issues in distributed control design, Cardinality minimization, Convex optimization, Distributed control, Sparsity-promoting optimal control, Spatially-invariant systems. [bibtex-entry]


  31. Y. Chen, M. R. Jovanovic, and T. T. Georgiou. State covariances and the matrix completion problem. In Proceedings of the 52nd IEEE Conference on Decision and Control, Florence, Italy, pages 1702-1707, 2013. Keyword(s): Convex optimization, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  32. F. Lin, M. R. Jovanovic, and T. T. Georgiou. An ADMM algorithm for matrix completion of partially known state covariances. In Proceedings of the 52nd IEEE Conference on Decision and Control, Florence, Italy, pages 1684-1689, 2013. Keyword(s): Alternating direction method of multipliers, Convex optimization, Low-rank approximation, Matrix completion problems, Nuclear norm regularization, Structured covariances. [bibtex-entry]


  33. M. R. Jovanovic, P. J. Schmid, and J. W. Nichols. Low-rank and sparse dynamic mode decomposition. In Center for Turbulence Research Annual Research Briefs, pages 139-152, 2012. Keyword(s): Dynamic Mode Decomposition, Flow modeling and control, Convex optimization, Sparsity. [bibtex-entry]


  34. M. Fardad, F. Lin, and M. R. Jovanovic. Algorithms for leader selection in large dynamical networks: noise-free leaders. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, Orlando, FL, pages 7188-7193, 2011. Keyword(s): Consensus networks, Convex optimization, Leader selection, Performance bounds, Sparsity. [bibtex-entry]


  35. F. Lin, M. Fardad, and M. R. Jovanovic. Algorithms for leader selection in large dynamical networks: noise-corrupted leaders. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, Orlando, FL, pages 2932-2937, 2011. Keyword(s): Alternating direction method of multipliers, Consensus networks, Convex optimization, Greedy algorithm, Leader selection, Performance bounds, Sparsity. [bibtex-entry]



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