Ion Necoara
Orcid: 0000-0003-1102-2654
According to our database1,
Ion Necoara
authored at least 102 papers
between 2004 and 2024.
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Bibliography
2024
Comput. Optim. Appl., May, 2024
Comput. Optim. Appl., March, 2024
Exact representation and efficient approximations of linear model predictive control laws via HardTanh type deep neural networks.
Syst. Control. Lett., 2024
Convergence analysis of stochastic higher-order majorization-minimization algorithms.
Optim. Methods Softw., 2024
Data-Driven Loewner Matrices-Based Modeling and Model Predictive Control of a Single Machine Infinite Bus Model.
Proceedings of the 32nd Mediterranean Conference on Control and Automation, 2024
Unified Analysis of Stochastic Gradient Projection Methods for Convex Optimization with Functional Constraints.
Proceedings of the European Control Conference, 2024
2023
SIAM J. Optim., September, 2023
An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization.
Proceedings of the European Control Conference, 2023
Modified projected Gauss-Newton method for constrained nonlinear least-squares: application to power flow analysis.
Proceedings of the European Control Conference, 2023
Dimensionality reduction of hyperspectral images using an ICA-based stochastic second-order optimization algorithm.
Proceedings of the European Control Conference, 2023
Deep unfolding projected first order methods-based architectures: application to linear model predictive control.
Proceedings of the European Control Conference, 2023
Can random proximal coordinate descent be accelerated on nonseparable convex composite minimization problems?
Proceedings of the European Control Conference, 2023
Control of a wastewater treatment process using linear and nonlinear model predictive control.
Proceedings of the 28th IEEE International Conference on Emerging Technologies and Factory Automation, 2023
Linearized ADMM for Nonsmooth Nonconvex Optimization with Nonlinear Equality Constraints.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
2022
Linear Convergence of Random Dual Coordinate Descent on Nonpolyhedral Convex Problems.
Math. Oper. Res., November, 2022
Stochastic Higher-Order Independent Component Analysis for Hyperspectral Dimensionality Reduction.
IEEE Trans. Computational Imaging, 2022
Stochastic block projection algorithms with extrapolation for convex feasibility problems.
Optim. Methods Softw., 2022
Stochastic subgradient for composite convex optimization with functional constraints.
J. Mach. Learn. Res., 2022
Autom., 2022
Proceedings of the 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2022
A Comparative Study of Compressive Sensing Algorithms for Hyperspectral Imaging Reconstruction.
Proceedings of the 14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, 2022
Proceedings of the 26th International Conference on System Theory, Control and Computing , 2022
Coordinate projected gradient descent minimization and its application to orthogonal nonnegative matrix factorization.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
2021
General Convergence Analysis of Stochastic First-Order Methods for Composite Optimization.
J. Optim. Theory Appl., 2021
Minibatch stochastic subgradient-based projection algorithms for feasibility problems with convex inequalities.
Comput. Optim. Appl., 2021
Proceedings of the 2021 European Control Conference, 2021
Proceedings of the 2021 European Control Conference, 2021
2020
IEEE Trans. Autom. Control., 2020
Comput. Optim. Appl., 2020
Proceedings of the 18th European Control Conference, 2020
A suboptimal H2 clustering-based model reduction approach for linear network systems.
Proceedings of the 18th European Control Conference, 2020
2019
Randomized Projection Methods for Convex Feasibility: Conditioning and Convergence Rates.
SIAM J. Optim., 2019
Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming.
Optim. Methods Softw., 2019
Math. Program., 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Parameter selection for best H<sub>2</sub> moment matching-based model approximation through gradient optimization.
Proceedings of the 17th European Control Conference, 2019
Proceedings of the 17th European Control Conference, 2019
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
2018
On the Convergence of Inexact Projection Primal First-Order Methods for Convex Minimization.
IEEE Trans. Autom. Control., 2018
OR-SAGA: Over-relaxed stochastic average gradient mapping algorithms for finite sum minimization.
Proceedings of the 16th European Control Conference, 2018
2017
Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization.
Optim. Lett., 2017
J. Optim. Theory Appl., 2017
Random Block Coordinate Descent Methods for Linearly Constrained Optimization over Networks.
J. Optim. Theory Appl., 2017
Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization.
J. Mach. Learn. Res., 2017
2016
Parallel Random Coordinate Descent Method for Composite Minimization: Convergence Analysis and Error Bounds.
SIAM J. Optim., 2016
Iteration complexity analysis of dual first-order methods for conic convex programming.
Optim. Methods Softw., 2016
Complexity certifications of inexact projection primal gradient method for convex problems: Application to embedded MPC.
Proceedings of the 24th Mediterranean Conference on Control and Automation, 2016
Optimal voltage control for loss minimization based on sequential convex programming.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference Europe, 2016
2015
IEEE Trans. Autom. Control., 2015
Computational complexity certification for dual gradient method: Application to embedded MPC.
Syst. Control. Lett., 2015
Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization.
J. Glob. Optim., 2015
On linear convergence of a distributed dual gradient algorithm for linearly constrained separable convex problems.
Autom., 2015
A fully distributed dual gradient method with linear convergence for large-scale separable convex problems.
Proceedings of the 14th European Control Conference, 2015
Random Coordinate Descent Methods for Sparse Optimization: Application to Sparse Control.
Proceedings of the 20th International Conference on Control Systems and Computer Science, 2015
Rate of convergence analysis of a dual fast gradient method for general convex optimization.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015
On the behavior of first-order penalty methods for conic constrained convex programming when Lagrange multipliers do not exist.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015
DuQuad: A toolbox for solving convex quadratic programs using dual (augmented) first order algorithms.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015
Distributed and parallel random coordinate descent methods for huge convex programming over networks.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015
Parallel and distributed random coordinate descent method for convex error bound minimization.
Proceedings of the American Control Conference, 2015
2014
IEEE Trans. Autom. Control., 2014
Computational Complexity of Inexact Gradient Augmented Lagrangian Methods: Application to Constrained MPC.
SIAM J. Control. Optim., 2014
Path-following gradient-based decomposition algorithms for separable convex optimization.
J. Glob. Optim., 2014
A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints.
Comput. Optim. Appl., 2014
On the lifting problems and their connections with piecewise affine control law design.
Proceedings of the 13th European Control Conference, 2014
A proximal alternating minimization method for ℓ0-regularized nonlinear optimization problems: application to state estimation.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014
2013
Random Coordinate Descent Algorithms for Multi-Agent Convex Optimization Over Networks.
IEEE Trans. Autom. Control., 2013
An Inexact Perturbed Path-Following Method for Lagrangian Decomposition in Large-Scale Separable Convex Optimization.
SIAM J. Optim., 2013
Proceedings of the 12th European Control Conference, 2013
A computationally efficient parallel coordinate descent algorithm for MPC: Implementation on a PLC.
Proceedings of the 12th European Control Conference, 2013
A dual decomposition algorithm for separable nonconvex optimization using the penalty function framework.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
Linear model predictive control based on approximate optimal control inputs and constraint tightening.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
Feasible distributed MPC scheme for network systems based on an inexact dual gradient method.
Proceedings of the 9th Asian Control Conference, 2013
Distributed model predictive control of leader-follower systems using an interior point method with efficient computations.
Proceedings of the American Control Conference, 2013
2012
Proceedings of the 51th IEEE Conference on Decision and Control, 2012
Suboptimal distributed MPC based on a block-coordinate descent method with feasibility and stability guarantees.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012
Proceedings of the 51th IEEE Conference on Decision and Control, 2012
Proceedings of the IEEE International Conference on Control Applications, 2012
Proceedings of the IEEE International Conference on Control Applications, 2012
2010
IEEE Trans. Signal Process., 2010
Fast primal-dual projected linear iterations for distributed consensus in constrained convex optimization.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010
2009
Proceedings of the Artificial Neural Networks, 2009
Proceedings of the 17th European Signal Processing Conference, 2009
A dual interior-point distributed algorithm for large-scale data networks optimization.
Proceedings of the 10th European Control Conference, 2009
Distributed nonlinear optimal control using sequential convex programming and smoothing techniques.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009
2008
IEEE Trans. Autom. Control., 2008
Every Continuous Nonlinear Control System Can be Obtained by Parametric Convex Programming.
IEEE Trans. Autom. Control., 2008
Int. J. Control, 2008
Stabilization of max-plus-linear systems using model predictive control: The unconstrained case.
Autom., 2008
Proceedings of the 47th IEEE Conference on Decision and Control, 2008
Application of the proximal center decomposition method to distributed model predictive control.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008
2007
IEEE Trans. Autom. Control., 2007
Discret. Event Dyn. Syst., 2007
2006
Proceedings of the 45th IEEE Conference on Decision and Control, 2006
Robust hybrid MPC applied to the design of an adaptive cruise controller for a road vehicle.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006
Proceedings of the American Control Conference, 2006
Stabilization of Max-plus-linear Systems using receding horizon control - the unconstrained Case.
Proceedings of the 2nd IFAC Conference on Analysis and Design of Hybrid Systems, 2006
2005
Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005
Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005
2004
Model predictive control for perturbed continuous piecewise affine systems with bounded disturbances.
Proceedings of the 43rd IEEE Conference on Decision and Control, 2004
Proceedings of the 2004 American Control Conference, 2004