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Publications about 'Convex optimization'


S. HassanMoghaddam.
Analysis, design, and optimization of largescale networks of dynamical systems.
PhD thesis,
University of Southern California,
2019.
Keyword(s): Consensus,
Control for optimization,
Convex Optimization,
Distributed control,
Forwardbackward envelope,
DouglasRachford splitting,
Global exponential stability,
Integral quadratic constraints,
Networks of dynamical systems,
Nonsmooth optimization,
PolyakLojasiewicz inequality,
Proximal algorithms,
Primaldual methods,
Proximal augmented Lagrangian,
Regularization for design,
Sparse graphs,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification,
Topology design.
[bibtexentry]

N. K. Dhingra.
Optimization and control of largescale networked systems.
PhD thesis,
University of Minnesota,
2017.
Keyword(s): Augmented Lagrangian,
Combination drug therapy,
Convex optimization,
Directed networks,
Leader selection,
Method of multipliers,
Nonsmooth optimization,
Optimization,
Proximal algorithms,
Proximal augmented Lagrangian,
Regularization,
Second order primaldual method,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification.
[bibtexentry]

A. Zare.
Lowcomplexity stochastic modeling of wallbounded shear flows.
PhD thesis,
University of Minnesota,
2016.
Keyword(s): Alternating minimization algorithm,
Colored noise,
Convex optimization,
Disturbance dynamics,
Flow modeling and control,
Lowcomplexity modeling,
Lowrank approximation,
Matrix completion problem,
Nuclear norm regularization,
Structured covariances,
Turbulence modeling.
[bibtexentry]

F. Lin.
Structure identification and optimal design of largescale 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,
Sparsitypromoting optimal control.
[bibtexentry]

H. Mohammadi,
M. Razaviyayn,
and M. R. Jovanovic.
Tradeoffs between convergence rate and noise amplification for momentumbased accelerated optimization algorithms.
2022.
Note: Submitted; also arXiv:2209.11920.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Gradient descent,
Heavyball method,
Nesterov's accelerated method,
Nonnormal dynamics,
Noise amplification,
Secondorder moments.
[bibtexentry]

H. Mohammadi,
S. Samuelson,
and M. R. Jovanovic.
Transient growth of accelerated optimization algorithms.
IEEE Trans. Automat. Control,
2022.
Note: Doi:10.1109/TAC.2022.3162154.
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]

S. HassanMoghaddam and M. R. Jovanovic.
Proximal gradient flow and DouglasRachford splitting dynamics: global exponential stability via integral quadratic constraints.
Automatica,
123:109311,
January 2021.
Keyword(s): Control for optimization,
Convex Optimization,
Forwardbackward envelope,
DouglasRachford splitting,
Global exponential stability,
Integral quadratic constraints,
Nonsmooth optimization,
PolyakLojasiewicz inequality,
Proximal algorithms,
Primaldual methods,
Proximal augmented Lagrangian.
[bibtexentry]

M. R. Jovanovic.
From bypass transition to flow control and datadriven turbulence modeling: An inputoutput viewpoint.
Annu. Rev. Fluid Mech.,
53(1):311345,
January 2021.
Keyword(s): Colored noise,
Convex optimization,
Drag reduction,
Energy amplification,
Flow modeling and control,
Inputoutput analysis,
Lowcomplexity modeling,
Lowrank approximation,
Matrix completion problems,
NavierStokes equations,
Nuclear norm regularization,
Simulationfree design,
Structured covariances,
Transition to turbulence,
Turbulence modeling.
[bibtexentry]

H. Mohammadi,
M. Razaviyayn,
and M. R. Jovanovic.
Robustness of accelerated firstorder algorithms for strongly convex optimization problems.
IEEE Trans. Automat. Control,
66(6):24802495,
June 2021.
Keyword(s): Accelerated firstorder algorithms,
Consensus networks,
Control for optimization,
Convex optimization,
Integral quadratic constraints,
Linear matrix inequalities,
Noise amplification,
Secondorder moments,
Semidefinite programming.
[bibtexentry]

D. Ding,
X. Wei,
Z. Yang,
Z. Wang,
and M. R. Jovanovic.
Fast multiagent temporaldifference learning via homotopy stochastic primaldual optimization.
IEEE Trans. Automat. Control,
2020.
Note: Submitted; also arXiv:1908.02805.
Keyword(s): Convex optimization,
Distributed temporaldifference learning,
Multiagent systems,
Primaldual algorithms,
Reinforcement learning,
Stochastic optimization.
[bibtexentry]

A. Zare,
T. T. Georgiou,
and M. R. Jovanovic.
Stochastic dynamical modeling of turbulent flows.
Annu. Rev. Control Robot. Auton. Syst.,
3:195219,
May 2020.
Keyword(s): Colored noise,
Convex optimization,
Disturbance dynamics,
Flow modeling and control,
Lowcomplexity modeling,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances,
Turbulence modeling.
[bibtexentry]

A. Zare,
H. Mohammadi,
N. K. Dhingra,
T. T. Georgiou,
and M. R. Jovanovic.
Proximal algorithms for largescale statistical modeling and sensor/actuator selection.
IEEE Trans. Automat. Control,
65(8):34413456,
August 2020.
Keyword(s): Actuator selection,
Augmented Lagrangian,
Convex optimization,
Lowrank perturbation,
Matrix completion problem,
Method of multipliers,
Nonsmooth optimization,
Proximal algorithms,
Regularization for design,
Sensor selection,
Sparsitypromoting optimal control,
Structured covariances.
[bibtexentry]

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):352362,
March 2019.
Keyword(s): Combination drug therapy,
Convex optimization,
Directed Networks,
Leader selection,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Topology design for stochasticallyforced consensus networks.
IEEE Trans. Control Netw. Syst.,
5(3):10751086,
September 2018.
Keyword(s): Consensus,
Convex optimization,
Distributed control,
Interior point method,
Proximal gradient method,
Proximal Newton method,
Sparse graphs,
Topology design.
[bibtexentry]

A. Zare,
Y. Chen,
M. R. Jovanovic,
and T. T. Georgiou.
Lowcomplexity modeling of partially available secondorder statistics: theory and an efficient matrix completion algorithm.
IEEE Trans. Automat. Control,
62(3):13681383,
March 2017.
Keyword(s): Alternating minimization algorithm,
Convex optimization,
Disturbance dynamics,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

A. Zare,
M. R. Jovanovic,
and T. T. Georgiou.
Colour of turbulence.
J. Fluid Mech.,
812:636680,
February 2017.
Keyword(s): Colored noise,
Convex optimization,
Disturbance dynamics,
Flow modeling and control,
Lowcomplexity modeling,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances,
Turbulence modeling.
[bibtexentry]

M. R. Jovanovic and N. K. Dhingra.
Controller architectures: tradeoffs between performance and structure.
Eur. J. Control,
30:7691,
July 2016.
Keyword(s): Controller architecture,
Convex optimization,
Distributed control,
Networks of dynamical systems,
Nonsmooth optimization,
Performance vs. complexity,
Regularization,
Sparsitypromoting optimal control,
Structured optimal control,
Structure identification.
[bibtexentry]

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

F. Lin,
M. Fardad,
and M. R. Jovanovic.
Algorithms for leader selection in stochastically forced consensus networks.
IEEE Trans. Automat. Control,
59(7):17891802,
July 2014.
Keyword(s): Alternating direction method of multipliers,
Consensus networks,
Convex optimization,
Greedy algorithm,
Leader selection,
Performance bounds,
Sparsity.
[bibtexentry]

R. Moarref,
M. R. Jovanovic,
J. A. Tropp,
A. S. Sharma,
and B. J. McKeon.
A loworder 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,
Lowrank approximation.
[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,
2023.
Note: Submitted.
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]

S. Samuelson,
H. Mohammadi,
and M. R. Jovanovic.
Performance of noisy higherorder accelerated gradient flow dynamics for strongly convex quadratic optimization problems.
In Proceedings of the 2023 American Control Conference,
San Diego, CA,
2023.
Note: Submitted.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convergence rate,
Convex optimization,
Gradient flow dynamics,
Noise amplification,
Nonnormal dynamics,
Twostep momentum algorithm.
[bibtexentry]

H. Mohammadi and M. R. Jovanovic.
On the noise amplification of primaldual gradient flow dynamics based on proximal augmented Lagrangian.
In Proceedings of the 2022 American Control Conference,
Atlanta, GA,
pages 926931,
2022.
Keyword(s): Control for optimization,
Convex Optimization,
Integral quadratic constraints,
Linear matrix inequalities,
Noise amplification,
Nonsmooth optimization,
Proximal algorithms,
Primaldual gradient flow dynamics,
Primaldual methods,
Proximal augmented Lagrangian,
Secondorder moments,
Semidefinite programming.
[bibtexentry]

I. K. Ozaslan,
S. HassanMoghaddam,
and M. R. Jovanovic.
On the asymptotic stability of proximal algorithms for convex optimization problems with multiple nonsmooth regularizers.
In Proceedings of the 2022 American Control Conference,
Atlanta, GA,
pages 132137,
2022.
Keyword(s): Control for optimization,
Convex Optimization,
DouglasRachford splitting,
Global asymptotic stability,
Lyapunovbased analysis,
Nonsmooth optimization,
Proximal algorithms,
Primaldual gradient flow dynamics,
Primaldual methods,
Proximal augmented Lagrangian.
[bibtexentry]

D. Ding,
X. Wei,
Z. Yang,
Z. Wang,
and M. R. Jovanovic.
Provably efficient safe exploration via primaldual policy optimization.
In 24th International Conference on Artificial Intelligence and Statistics,
volume 130,
Virtual,
pages 33043312,
2021.
Keyword(s): Safe reinforcement learning,
Constrained Markov decision processes,
Safe exploration,
Proximal policy optimization,
Nonconvex optimization,
Online mirror descent,
Primaldual method.
[bibtexentry]

D. Ding and M. R. Jovanovic.
Global exponential stability of primaldual gradient flow dynamics based on the proximal augmented Lagrangian: A Lyapunovbased approach.
In Proceedings of the 59th IEEE Conference on Decision and Control,
Jeju Island, Republic of Korea,
pages 48364841,
2020.
Keyword(s): Augmented Lagrangian,
Control for optimization,
Convex optimization,
Global exponential stability,
Lyapunovbased approach,
Nonsmooth optimization,
Primaldual gradient flow dynamics,
Primaldual methods,
Proximal augmented Lagrangian.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Global exponential stability of the DouglasRachford splitting dynamics.
In Preprints of the 21st IFAC World Congress,
Berlin, Germany,
pages 73507354,
2020.
Keyword(s): Control for optimization,
Convex Optimization,
Forwardbackward envelope,
DouglasRachford splitting,
Global exponential stability,
Integral quadratic constraints,
Nonsmooth optimization,
PolyakLojasiewicz inequality,
Proximal algorithms,
Primaldual methods,
Proximal augmented Lagrangian.
[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]

D. Ding and M. R. Jovanovic.
Global exponential stability of primaldual gradient flow dynamics based on the proximal augmented Lagrangian.
In Proceedings of the 2019 American Control Conference,
Philadelphia, PA,
pages 34143419,
2019.
Keyword(s): Convex optimization,
Global exponential stability,
Nonsmooth optimization,
Primaldual gradient flow dynamics,
Proximal augmented Lagrangian method.
[bibtexentry]

D. Ding,
X. Wei,
Z. Yang,
Z. Wang,
and M. R. Jovanovic.
Fast multiagent temporaldifference learning via homotopy stochastic primaldual method.
In Optimization Foundations for Reinforcement Learning Workshop, 33rd Conference on Neural Information Processing Systems,
Vancouver, Canada,
2019.
Keyword(s): Convex optimization,
Distributed temporaldifference learning,
Multiagent systems,
Primaldual algorithms,
Reinforcement learning,
Stochastic optimization.
[bibtexentry]

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 34263431,
2019.
Keyword(s): Accelerated firstorder algorithms,
Control for optimization,
Convex optimization,
Integral quadratic constraints,
Linear matrix inequalities,
Noise amplification,
Secondorder moments,
Semidefinite programming.
[bibtexentry]

D. Ding,
B. Hu,
N. K. Dhingra,
and M. R. Jovanovic.
An exponentially convergent primaldual algorithm for nonsmooth composite minimization.
In Proceedings of the 57th IEEE Conference on Decision and Control,
Miami, FL,
pages 49274932,
2018.
Keyword(s): Control for optimization,
Convex optimization,
Euler discretization,
Exponential convergence,
Global exponential stability,
Integral quadratic constraints,
Proximal augmented Lagrangian,
Nonsmooth optimization,
Primaldual gradient flow dynamics,
Proximal algorithms,
Regularization.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
Topology identification via growing a ChowLiu tree network.
In Proceedings of the 57th IEEE Conference on Decision and Control,
Miami, FL,
pages 54215426,
2018.
Keyword(s): ChowLiu tree,
Consensus,
Convex optimization,
Graphical LASSO,
Sparse graphs,
Topology identification,
Maximum likelihood,
Sparse inverse covariance estimation.
[bibtexentry]

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 65146519,
2018.
Keyword(s): Convex optimization,
Proximal algorithms,
Sensor selection,
Semidefinite programming,
Sparsitypromoting estimation and control,
QuasiNewton methods.
[bibtexentry]

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 37753780,
2017.
Keyword(s): Augmented Lagrangian,
Convex optimization,
Lowrank perturbation,
Matrix completion problem,
Method of multipliers,
Nonsmooth optimization,
Proximal methods,
Regularization,
Sparsitypromoting optimal control,
Structured covariances.
[bibtexentry]

J. Annoni,
P. Seiler,
and M. R. Jovanovic.
Sparsitypromoting dynamic mode decomposition for systems with inputs.
In Proceedings of the 55th IEEE Conference on Decision and Control,
Las Vegas, NV,
pages 65066511,
2016.
Note: (Invited paper).
Keyword(s): Dynamic Mode Decomposition,
Flow modeling and control,
Convex optimization,
Sparsity.
[bibtexentry]

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 411413,
2016.
Note: (Invited paper).
Keyword(s): Convex optimization,
Networks,
Monotone systems,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design.
[bibtexentry]

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 52635268,
2016.
Note: (Invited paper).
Keyword(s): Combination drug therapy,
Convex optimization,
Networks,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design,
Robust Control.
[bibtexentry]

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 27152720,
2016.
Note: (Invited paper).
Keyword(s): Consensus networks,
Convex optimization,
Positive systems,
Leader selection.
[bibtexentry]

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 825830,
2016.
Keyword(s): Combination drug therapy,
Convex optimization,
Leader selection,
Networks,
Positive systems,
Proximal algorithms,
Optimization,
Sparsitypromoting optimal control,
Structured design.
[bibtexentry]

N. K. Dhingra,
X. Wu,
and M. R. Jovanovic.
Sparsitypromoting optimal control of systems with invariances and symmetries.
In Proceedings of the 10th IFAC Symposium on Nonlinear Control Systems,
Monterey, CA,
pages 648653,
2016.
Keyword(s): Architectural issues in distributed control design,
Cardinality minimization,
Convex optimization,
Distributed control,
Sparsitypromoting optimal control,
Spatiallyinvariant systems,
Symmetric systems.
[bibtexentry]

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 19781983,
2016.
Keyword(s): Convex optimization,
$k$supportnorm,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

S. HassanMoghaddam,
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 46244629,
2016.
Keyword(s): Consensus,
Convex optimization,
Sparse graphs,
Topology identification,
Maximum likelihood,
Sparse inverse covariance estimation.
[bibtexentry]

S. HassanMoghaddam 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 986991,
2016.
Keyword(s): Convex optimization,
Coordinate descent algorithm,
Networks,
Proximal algorithms.
[bibtexentry]

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 117119,
2016.
Keyword(s): Alternating minimization algorithm,
Convex optimization,
Disturbance dynamics,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

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 70367041,
2016.
Keyword(s): Convex optimization,
Lowrank perturbation,
Matrix completion problems,
Sparsitypromoting optimal control,
Structured covariances.
[bibtexentry]

S. HassanMoghaddam and M. R. Jovanovic.
An interior point method for growing connected resistive networks.
In Proceedings of the 2015 American Control Conference,
Chicago, IL,
pages 12231228,
2015.
Keyword(s): Consensus,
Convex optimization,
Distributed control,
Interior point method,
Sparse graphs,
Topology design.
[bibtexentry]

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 515520,
2015.
Keyword(s): Alternating direction method of multipliers,
Alternating minimization algorithm,
Convex optimization,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

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 40394044,
2014.
Note: (Invited paper).
Keyword(s): Alternating direction method of multipliers,
Convex optimization,
Actuator selection,
Sensor selection.
[bibtexentry]

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 24382443,
2014.
Keyword(s): Architectural issues in distributed control design,
Cardinality minimization,
Convex optimization,
Distributed control,
Sparsitypromoting optimal control.
[bibtexentry]

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 16801685,
2014.
Note: (Invited paper; Finalist, Best Student Paper Award).
Keyword(s): Alternating direction method of multipliers,
Convex optimization,
Flow modeling and control,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

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 345354,
2014.
Keyword(s): Convex optimization,
Flow modeling and control,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

D. M. Zoltowski,
N. K. Dhingra,
F. Lin,
and M. R. Jovanovic.
Sparsitypromoting optimal control of spatiallyinvariant systems.
In Proceedings of the 2014 American Control Conference,
Portland, OR,
pages 12611266,
2014.
Keyword(s): Architectural issues in distributed control design,
Cardinality minimization,
Convex optimization,
Distributed control,
Sparsitypromoting optimal control,
Spatiallyinvariant systems.
[bibtexentry]

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 17021707,
2013.
Keyword(s): Convex optimization,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

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 16841689,
2013.
Keyword(s): Alternating direction method of multipliers,
Convex optimization,
Lowrank approximation,
Matrix completion problems,
Nuclear norm regularization,
Structured covariances.
[bibtexentry]

M. R. Jovanovic,
P. J. Schmid,
and J. W. Nichols.
Lowrank and sparse dynamic mode decomposition.
In Center for Turbulence Research Annual Research Briefs,
pages 139152,
2012.
Keyword(s): Dynamic Mode Decomposition,
Flow modeling and control,
Convex optimization,
Sparsity.
[bibtexentry]

M. Fardad,
F. Lin,
and M. R. Jovanovic.
Algorithms for leader selection in large dynamical networks: noisefree leaders.
In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference,
Orlando, FL,
pages 71887193,
2011.
Keyword(s): Consensus networks,
Convex optimization,
Leader selection,
Performance bounds,
Sparsity.
[bibtexentry]

F. Lin,
M. Fardad,
and M. R. Jovanovic.
Algorithms for leader selection in large dynamical networks: noisecorrupted leaders.
In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference,
Orlando, FL,
pages 29322937,
2011.
Keyword(s): Alternating direction method of multipliers,
Consensus networks,
Convex optimization,
Greedy algorithm,
Leader selection,
Performance bounds,
Sparsity.
[bibtexentry]
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Last modified: Sun Oct 23 23:45:07 2022
Author: mihailo.
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