Ion Necoara - RankMe

119 papers A* 1C 7Journal 55Unranked 56

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Convergence rates for an inexact linearized ADMM for nonsmooth nonconvex optimization with nonlinear equality constraints. Comput. Optim. Appl. Lahcen El Bourkhissi, Ion Necoara
2026	J	`jnl`	Moving Higher-Order Taylor Approximations Method for Smooth Constrained Minimization Problems. SIAM J. Optim. Yassine Nabou, Ion Necoara
2025	J	`jnl`	A Systematic Approach to General Higher-Order Majorization-Minimization Algorithms for (Non)convex Optimization. SIAM J. Optim. Ion Necoara, Daniela Lupu
2025	—	`conf`	A stochastic augumented Lagrangian algorithm for smooth convex optimization: application to MPC with quadratic constraints. MED Nitesh Kumar Singh, Daniela Lupu, Ion Necoara
2025	J	`jnl`	An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization. CoRR Lionel Tondji, Dirk A. Lorenz, Ion Necoara
2025	J	`jnl`	Complexity of linearized quadratic penalty for optimization with nonlinear equality constraints. J. Glob. Optim. Lahcen El Bourkhissi, Ion Necoara
2025	—	`conf`	Convergence rates of ℓq penalty methods for nonsmooth nonconvex optimization with nonlinear equality constraints. CDC Lahcen El Bourkhissi, Ion Necoara
2025	—	`conf`	Deep unfolding primal-dual architectures: application to linear model predictive control. MED Daniela Lupu, Ion Necoara, Lucian Toma
2025	J	`jnl`	Efficiency of Stochastic Coordinate Proximal Gradient Methods on Nonseparable Composite Optimization. Math. Oper. Res. Ion Necoara, Flávia Chorobura
2025	J	`jnl`	Erratum to: Linear Convergence of Dual Coordinate Descent on Nonpolyhedral Convex Problems. Math. Oper. Res. Ion Necoara, Olivier Fercoq
2025	—	`conf`	Moment matching-based model reduction for systems with linear quadratic output. CDC Tudor C. Ionescu, Orest V. Iftime, Ion Necoara
2025	J	`jnl`	Proximal gradient methods with inexact oracle of degree q for composite optimization. Optim. Lett. Yassine Nabou, François Glineur, Ion Necoara
2025	J	`jnl`	Quick Unsupervised Hyperspectral Dimensionality Reduction for Earth Observation: A Comparison. IEEE Trans. Computational Imaging Daniela Lupu, Joseph L. Garrett, Tor Arne Johansen, Milica Orlandic, Ion Necoara
2025	J	`jnl`	Stochastic Halfspace Approximation Method for Convex Optimization With Nonsmooth Functional Constraints. IEEE Trans. Autom. Control. Nitesh Kumar Singh, Ion Necoara
2024	J	`jnl`	A Comparative Study of Compressive Sensing Algorithms for Hyperspectral Imaging Reconstruction. CoRR Jon Álvarez Justo, Daniela Lupu, Milica Orlandic, Ion Necoara, Tor Arne Johansen
2024	J	`jnl`	A stochastic moving ball approximation method for smooth convex constrained minimization. Comput. Optim. Appl. Nitesh Kumar Singh, Ion Necoara
2024	J	`jnl`	Convergence analysis of stochastic higher-order majorization-minimization algorithms. Optim. Methods Softw. Daniela Lupu, Ion Necoara
2024	J	`jnl`	Coordinate descent methods beyond smoothness and separability. Comput. Optim. Appl. Flávia Chorobura, Ion Necoara
2024	—	`conf`	Data-Driven Loewner Matrices-Based Modeling and Model Predictive Control of a Single Machine Infinite Bus Model. MED Tudor C. Ionescu, Orest V. Iftime, Ion Necoara
2024	J	`jnl`	Efficiency of higher-order algorithms for minimizing composite functions. Comput. Optim. Appl. Yassine Nabou, Ion Necoara
2024	J	`jnl`	Exact representation and efficient approximations of linear model predictive control laws via HardTanh type deep neural networks. Syst. Control. Lett. Daniela Lupu, Ion Necoara
2024	—	`conf`	Moment matching for second-order systems with pole-zero placement. CDC X. Cheng, Tudor C. Ionescu, Orest V. Iftime, Ion Necoara
2024	—	`conf`	Unified Analysis of Stochastic Gradient Projection Methods for Convex Optimization with Functional Constraints. ECC Nitesh Kumar Singh, Ion Necoara
2023	J	`jnl`	Acceleration and restart for the randomized Bregman-Kaczmarz method. CoRR Lionel Tondji, Ion Necoara, Dirk A. Lorenz
2023	—	`conf`	An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization. ECC Lionel Tondji, Dirk A. Lorenz, Ion Necoara
2023	—	`conf`	Can random proximal coordinate descent be accelerated on nonseparable convex composite minimization problems? ECC Flávia Chorobura, François Glineur, Ion Necoara
2023	C	`conf`	Control of a wastewater treatment process using linear and nonlinear model predictive control. ETFA Liliana Maria Ghinea, Daniela Lupu, Marian Barbu, Ion Necoara
2023	—	`conf`	Deep unfolding projected first order methods-based architectures: application to linear model predictive control. ECC Daniela Lupu, Ion Necoara
2023	—	`conf`	Dimensionality reduction of hyperspectral images using an ICA-based stochastic second-order optimization algorithm. ECC Daniela Lupu, Ion Necoara, Tudor C. Ionescu, Liliana Maria Ghinea, Joseph L. Garrett, Tor Arne Johansen
2023	—	`conf`	Linearized ADMM for Nonsmooth Nonconvex Optimization with Nonlinear Equality Constraints. CDC Lahcen El Bourkhissi, Ion Necoara, Panagiotis Patrinos
2023	—	`conf`	Modified projected Gauss-Newton method for constrained nonlinear least-squares: application to power flow analysis. ECC Yassine Nabou, Lucian Toma, Ion Necoara
2023	J	`jnl`	Random Coordinate Descent Methods for Nonseparable Composite Optimization. SIAM J. Optim. Flávia Chorobura, Ion Necoara
2022	—	`conf`	A Comparative Study of Compressive Sensing Algorithms for Hyperspectral Imaging Reconstruction. IVMSP Jon Álvarez Justo, Daniela Lupu, Milica Orlandic, Ion Necoara, Tor Arne Johansen
2022	—	`conf`	Accelerating Support Vector Machines For Remote Platforms By Increasing Sparsity. WHISPERS Joseph L. Garrett, Nitesh Kumar Singh, Tor Arne Johansen, Ion Necoara
2022	—	`conf`	Coordinate projected gradient descent minimization and its application to orthogonal nonnegative matrix factorization. CDC Flávia Chorobura, Daniela Lupu, Ion Necoara
2022	—	`conf`	Least squares moment matching-based model reduction using convex optimization. ICSTCC Tudor C. Ionescu, Lahcen El Bourkhissi, Ion Necoara
2022	J	`jnl`	Linear Convergence of Random Dual Coordinate Descent on Nonpolyhedral Convex Problems. Math. Oper. Res. Ion Necoara, Olivier Fercoq
2022	J	`jnl`	Model reduction with pole-zero placement and high order moment matching. Autom. Tudor C. Ionescu, Orest V. Iftime, Ion Necoara
2022	J	`jnl`	Stochastic Higher-Order Independent Component Analysis for Hyperspectral Dimensionality Reduction. IEEE Trans. Computational Imaging Daniela Lupu, Ion Necoara, Joseph L. Garrett, Tor Arne Johansen
2022	J	`jnl`	Stochastic block projection algorithms with extrapolation for convex feasibility problems. Optim. Methods Softw. Ion Necoara
2022	J	`jnl`	Stochastic subgradient for composite convex optimization with functional constraints. J. Mach. Learn. Res. Ion Necoara, Nitesh Kumar Singh
2021	J	`jnl`	General Convergence Analysis of Stochastic First-Order Methods for Composite Optimization. J. Optim. Theory Appl. Ion Necoara
2021	—	`conf`	Local linear convergence of stochastic higher-order methods for convex optimization. ECC Daniela Lupu, Ion Necoara
2021	J	`jnl`	Minibatch stochastic subgradient-based projection algorithms for feasibility problems with convex inequalities. Comput. Optim. Appl. Ion Necoara, Angelia Nedic
2021	—	`conf`	Random coordinate descent methods for non-separable composite optimization. ECC Liliana Maria Ghinea, Ion Necoara, Marian Barbu
2020	J	`jnl`	$H_2$ Model Reduction of Linear Network Systems by Moment Matching and Optimization. IEEE Trans. Autom. Control. Ion Necoara, Tudor C. Ionescu
2020	—	`conf`	A suboptimal H2 clustering-based model reduction approach for linear network systems. ECC Xiaodong Cheng, Ion Necoara
2020	J	`jnl`	Composite convex optimization with global and local inexact oracles. Comput. Optim. Appl. Tianxiao Sun, Ion Necoara, Quoc Tran-Dinh
2020	—	`conf`	Optimal time-domain moment matching with partial placement of poles and zeros. ECC Tudor C. Ionescu, Orest V. Iftime, Ion Necoara
2019	A*	`conf`	Almost surely constrained convex optimization. ICML Olivier Fercoq, Ahmet Alacaoglu, Ion Necoara, Volkan Cevher
2019	J	`jnl`	Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming. Optim. Methods Softw. Ion Necoara, Andrei Patrascu, François Glineur
2019	J	`jnl`	Faster Randomized Block Kaczmarz Algorithms. SIAM J. Matrix Anal. Appl. Ion Necoara
2019	J	`jnl`	Linear convergence of first order methods for non-strongly convex optimization. Math. Program. Ion Necoara, Yurii E. Nesterov, François Glineur
2019	—	`conf`	Parameter selection for best H ECC Ion Necoara, Tudor C. Ionescu
2019	—	`conf`	Random gradient algorithms for convex minimization over intersection of simple sets. ECC Ion Necoara
2019	—	`conf`	Random minibatch projection algorithms for convex feasibility problems. CDC Angelia Nedic, Ion Necoara
2019	J	`jnl`	Randomized Projection Methods for Convex Feasibility: Conditioning and Convergence Rates. SIAM J. Optim. Ion Necoara, Peter Richtárik, Andrei Patrascu
2018	—	`conf`	OR-SAGA: Over-relaxed stochastic average gradient mapping algorithms for finite sum minimization. ECC Ion Necoara, Andrei Patrascu
2018	J	`jnl`	On the Convergence of Inexact Projection Primal First-Order Methods for Convex Minimization. IEEE Trans. Autom. Control. Andrei Patrascu, Ion Necoara
2017	J	`jnl`	Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization. Optim. Lett. Andrei Patrascu, Ion Necoara, Quoc Tran-Dinh
2017	J	`jnl`	Constructive Solution of Inverse Parametric Linear/Quadratic Programming Problems. J. Optim. Theory Appl. Ngoc Anh Nguyen, Sorin Olaru, Pedro Rodríguez-Ayerbe, Morten Hovd, Ion Necoara
2017	J	`jnl`	Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization. J. Mach. Learn. Res. Andrei Patrascu, Ion Necoara
2017	J	`jnl`	Random Block Coordinate Descent Methods for Linearly Constrained Optimization over Networks. J. Optim. Theory Appl. Ion Necoara, Yurii E. Nesterov, François Glineur
2016	—	`conf`	Complexity certifications of inexact projection primal gradient method for convex problems: Application to embedded MPC. MED Andrei Patrascu, Ion Necoara
2016	J	`jnl`	Iteration complexity analysis of dual first-order methods for conic convex programming. Optim. Methods Softw. Ion Necoara, Andrei Patrascu
2016	—	`conf`	Optimal voltage control for loss minimization based on sequential convex programming. ISGT Europe Ion Necoara, Valentin Nedelcu, Dragos N. Clipici, Lucian Toma, Constantin Bulac
2016	J	`jnl`	Parallel Random Coordinate Descent Method for Composite Minimization: Convergence Analysis and Error Bounds. SIAM J. Optim. Ion Necoara, Dragos N. Clipici
2015	—	`conf`	A fully distributed dual gradient method with linear convergence for large-scale separable convex problems. ECC Ion Necoara, Angelia Nedich
2015	J	`jnl`	Computational complexity certification for dual gradient method: Application to embedded MPC. Syst. Control. Lett. Ion Necoara
2015	—	`conf`	Distributed and parallel random coordinate descent methods for huge convex programming over networks. CDC Ion Necoara
2015	—	`conf`	DuQuad: A toolbox for solving convex quadratic programs using dual (augmented) first order algorithms. CDC Ion Necoara, Sverre Kvamme
2015	J	`jnl`	Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization. J. Glob. Optim. Andrei Patrascu, Ion Necoara
2015	J	`jnl`	On linear convergence of a distributed dual gradient algorithm for linearly constrained separable convex problems. Autom. Ion Necoara, Valentin Nedelcu
2015	—	`conf`	On the behavior of first-order penalty methods for conic constrained convex programming when Lagrange multipliers do not exist. CDC Ion Necoara, Andrei Patrascu
2015	C	`conf`	Parallel and distributed random coordinate descent method for convex error bound minimization. ACC Ion Necoara, Rolf Findeisen
2015	—	`conf`	Random Coordinate Descent Methods for Sparse Optimization: Application to Sparse Control. CSCS Andrei Patrascu, Ion Necoara
2015	J	`jnl`	Random Coordinate Descent Methods for ℓ IEEE Trans. Autom. Control. Andrei Patrascu, Ion Necoara
2015	—	`conf`	Rate of convergence analysis of a dual fast gradient method for general convex optimization. CDC Andrei Patrascu, Ion Necoara, Rolf Findeisen
2014	—	`conf`	A proximal alternating minimization method for ℓ0-regularized nonlinear optimization problems: application to state estimation. CDC Andrei Patrascu, Ion Necoara, Panagiotis Patrinos
2014	J	`jnl`	A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints. Comput. Optim. Appl. Ion Necoara, Andrei Patrascu
2014	J	`jnl`	Computational Complexity of Inexact Gradient Augmented Lagrangian Methods: Application to Constrained MPC. SIAM J. Control. Optim. Valentin Nedelcu, Ion Necoara, Quoc Tran-Dinh
2014	—	`conf`	On the lifting problems and their connections with piecewise affine control law design. ECC Ngoc Anh Nguyen, Sorin Olaru, Pedro Rodríguez-Ayerbe, Morten Hovd, Ion Necoara
2014	J	`jnl`	Path-following gradient-based decomposition algorithms for separable convex optimization. J. Glob. Optim. Dinh Quoc Tran, Ion Necoara, Moritz Diehl
2014	J	`jnl`	Rate Analysis of Inexact Dual First-Order Methods Application to Dual Decomposition. IEEE Trans. Autom. Control. Ion Necoara, Valentin Nedelcu
2013	—	`conf`	A computationally efficient parallel coordinate descent algorithm for MPC: Implementation on a PLC. ECC Ion Necoara, Dragos N. Clipici
2013	—	`conf`	A dual decomposition algorithm for separable nonconvex optimization using the penalty function framework. CDC Dinh Quoc Tran, Ion Necoara, Moritz Diehl
2013	—	`conf`	A random coordinate descent algorithm for large-scale sparse nonconvex optimization. ECC Andrei Patrascu, Ion Necoara
2013	J	`jnl`	An Inexact Perturbed Path-Following Method for Lagrangian Decomposition in Large-Scale Separable Convex Optimization. SIAM J. Optim. Dinh Quoc Tran, Ion Necoara, Carlo Savorgnan, Moritz Diehl
2013	C	`conf`	Distributed model predictive control of leader-follower systems using an interior point method with efficient computations. ACC Ion Necoara, Dragos N. Clipici, Sorin Olaru
2013	—	`conf`	Feasible distributed MPC scheme for network systems based on an inexact dual gradient method. ASCC Ion Necoara, Valentin Nedelcu, Dragos N. Clipici
2013	—	`conf`	Linear model predictive control based on approximate optimal control inputs and constraint tightening. CDC Ion Necoara, Valentin Nedelcu, Tamás Keviczky, Minh Dang Doan, Bart De Schutter
2013	J	`jnl`	Random Coordinate Descent Algorithms for Multi-Agent Convex Optimization Over Networks. IEEE Trans. Autom. Control. Ion Necoara
2012	—	`conf`	A random coordinate descent method for large-scale resource allocation problems. CDC Ion Necoara
2012	C	`conf`	An adaptive approximation method for Hammerstein systems identification. CCA Mihai Cornoiu, Ion Necoara
2012	—	`conf`	Iteration complexity of an inexact augmented Lagrangian method for constrained MPC. CDC Valentin Nedelcu, Ion Necoara
2012	C	`conf`	Networked control strategies for a 3 dimensional crane. CCA Adrian-Bogdan Hanchevici, Ion Necoara
2012	—	`conf`	Suboptimal distributed MPC based on a block-coordinate descent method with feasibility and stability guarantees. CDC Ion Necoara
2010	—	`conf`	Fast primal-dual projected linear iterations for distributed consensus in constrained convex optimization. CDC Ion Necoara, Ioan Dumitrache, Johan A. K. Suykens
2010	J	`jnl`	Improved dual decomposition based optimization for DSL dynamic spectrum management. IEEE Trans. Signal Process. Paschalis Tsiaflakis, Ion Necoara, Johan A. K. Suykens, Marc Moonen
2009	—	`conf`	A dual interior-point distributed algorithm for large-scale data networks optimization. ECC Ion Necoara, Johan A. K. Suykens
2009	—	`conf`	An improved dual decomposition approach to DSL dynamic spectrum management. EUSIPCO Paschalis Tsiaflakis, Ion Necoara, Johan A. K. Suykens, Marc Moonen
2009	—	`conf`	Distributed Control over Networks Using Smoothing Techniques. ICANN (2) Ion Necoara
2009	—	`conf`	Distributed nonlinear optimal control using sequential convex programming and smoothing techniques. CDC Ion Necoara, Carlo Savorgnan, Dinh Quoc Tran, Johan A. K. Suykens, Moritz Diehl
2008	—	`conf`	A proximal center-based decomposition method for multi-agent convex optimization. CDC Ion Necoara, Johan A. K. Suykens
2008	J	`jnl`	Application of a Smoothing Technique to Decomposition in Convex Optimization. IEEE Trans. Autom. Control. Ion Necoara, Johan A. K. Suykens
2008	—	`conf`	Application of the proximal center decomposition method to distributed model predictive control. CDC Ion Necoara, Minh Dang Doan, Johan A. K. Suykens
2008	J	`jnl`	Every Continuous Nonlinear Control System Can be Obtained by Parametric Convex Programming. IEEE Trans. Autom. Control. Michel Baes, Moritz Diehl, Ion Necoara
2008	J	`jnl`	Model predictive control for uncertain max-min-plus-scaling systems. Int. J. Control Ion Necoara, Bart De Schutter, Ton J. J. van den Boom, Hans Hellendoorn
2008	J	`jnl`	Stabilization of max-plus-linear systems using model predictive control: The unconstrained case. Autom. Ion Necoara, Ton J. J. van den Boom, Bart De Schutter, Hans Hellendoorn
2007	J	`jnl`	Finite-Horizon Min-Max Control of Max-Plus-Linear Systems. IEEE Trans. Autom. Control. Ion Necoara, Eric C. Kerrigan, Bart De Schutter, Ton J. J. van den Boom
2007	J	`jnl`	Stable Model Predictive Control for Constrained Max-Plus-Linear Systems. Discret. Event Dyn. Syst. Ion Necoara, Bart De Schutter, Ton J. J. van den Boom, Hans Hellendoorn
2006	—	`conf`	Robust hybrid MPC applied to the design of an adaptive cruise controller for a road vehicle. CDC Daniele Corona, Ion Necoara, Bart De Schutter, Ton J. J. van den Boom
2006	—	`conf`	Stabilization of Max-plus-linear Systems using receding horizon control - the unconstrained Case. ADHS Ion Necoara, Ton J. J. van den Boom, Bart De Schutter, Johannes Hellendoorn
2006	C	`conf`	Stable receding horizon control for max-plus-linear systems. ACC Ion Necoara, Bart De Schutter, Ton J. J. van den Boom, Johannes Hellendoorn
2006	—	`conf`	Worst-case optimal control of uncertain max-plus-linear systems. CDC Ion Necoara, Eric C. Kerrigan, Bart De Schutter, Ton J. J. van den Boom
2005	—	`conf`	On MPC for max-plus-linear systems: Analytic solution and stability. CDC/ECC Ton J. J. van den Boom, Bart De Schutter, Ion Necoara
2005	—	`conf`	Robustly stabilizing MPC for perturbed PWL systems. CDC/ECC Ion Necoara, Bart De Schutter, Ton J. J. van den Boom, Johannes Hellendoorn
2004	—	`conf`	Model predictive control for perturbed continuous piecewise affine systems with bounded disturbances. CDC Ion Necoara, Bart De Schutter, Ton J. J. van den Boom, Johannes Hellendoorn
2004	C	`conf`	On structural properties of Helbing's gas-kinetic traffic flow model. ACC Ion Necoara, Bart De Schutter, Hans Hellendoorn