Search Results - "Necoara, I."

Linear convergence of first order methods for non-strongly convex optimization by Necoara, I., Nesterov, Yu, Glineur, F.

“…The standard assumption for proving linear convergence of first order methods for smooth convex optimization is the strong convexity of the objective function,…”
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Stochastic block projection algorithms with extrapolation for convex feasibility problems by Necoara, I.

“…The stochastic alternating projection (SP) algorithm is a simple but powerful approach for solving convex feasibility problems. At each step, the method…”
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Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming by Necoara, I., Patrascu, A., Glineur, F.

“…In this paper we present a complete iteration complexity analysis of inexact first-order Lagrangian and penalty methods for solving cone-constrained convex…”
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Application of a Smoothing Technique to Decomposition in Convex Optimization by Necoara, I., Suykens, J.

“…Dual decomposition is a powerful technique for deriving decomposition schemes for convex optimization problems with separable structure. Although the augmented…”
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Iteration complexity analysis of dual first-order methods for conic convex programming by Necoara, I., Patrascu, A.

“…In this paper we provide a detailed analysis of the iteration complexity of dual first-order methods for solving conic convex problems. When it is difficult to…”
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Constructive Solution of Inverse Parametric Linear/Quadratic Programming Problems by Nguyen, N. A., Olaru, S., Rodriguez-Ayerbe, P., Hovd, M., Necoara, I.

“…Parametric convex programming has received a lot of attention, since it has many applications in chemical engineering, control engineering, signal processing,…”
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Fast inexact decomposition algorithms for large-scale separable convex optimization by Tran-Dinh, Q., Necoara, I., Diehl, M.

“…In this paper, we propose a new inexact dual decomposition algorithm for solving separable convex optimization problems. This algorithm is a combination of…”
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Interior-Point Lagrangian Decomposition Method for Separable Convex Optimization by Necoara, I., Suykens, J. A. K.

“…In this paper, we propose a distributed algorithm for solving large-scale separable convex problems using Lagrangian dual decomposition and the interior-point…”
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Every Continuous Nonlinear Control System Can be Obtained by Parametric Convex Programming by Baes, M., Diehl, M., Necoara, I.

“…In this short note, we define parametric convex programming (PCP) in a slightly different manner than it is usually done by extending convexity not only to…”
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Data-Driven Loewner Matrices-Based Modeling and Model Predictive Control of a Single Machine Infinite Bus Model by Ionescu, T. C., Iftime, O. V., Necoara, I.

“…In this paper, we consider the problem of data-driven modelling and model predictive control (MPC) of a single machine infinite bus system (SMIB). When a…”
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Model predictive control for uncertain max-min-plus-scaling systems by Necoara, I., De Schutter, B., Van Den Boom, T., Hellendoorn, H.

“…In this paper we extend the classical min-max model predictive control framework to a class of uncertain discrete event systems that can be modelled using the…”
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Finite-Horizon Min-Max Control of Max-Plus-Linear Systems by Necoara, I., Kerrigan, E.C., De Schutter, B., van den Boom, T.J.J.

“…In this note, we provide a solution to a class of finite-horizon min-max control problems for uncertain max-plus-linear systems where the uncertain parameters…”
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Accelerating Support Vector Machines For Remote Platforms By Increasing Sparsity by Garrett, J. L., Singh, N. K., Johansen, T. A., Necoara, I.

“…The support vector machine (SVM) classification algorithm often achieves quite high accuracy on hyperspectral images, even when trained on small amounts of…”
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Structural Properties of Helbing's Traffic Flow Model by Necoara, I., De Schutter, B., Hellendoorn, J.

“…The structural properties of the shock- and rarefaction-wave solutions of a macroscopic, second-order nonlocal continuum traffic flow model, namely, Helbing's…”
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Improved Dual Decomposition Based Optimization for DSL Dynamic Spectrum Management by Tsiaflakis, P., Necoara, I., Suykens, J., Moonen, M.

“…Dynamic spectrum management (DSM) has been recognized as a key technology to significantly improve the performance of digital subscriber line (DSL) broadband…”
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Efficiency of stochastic coordinate proximal gradient methods on nonseparable composite optimization by Necoara, I, Chorobura, F

“…This paper deals with composite optimization problems having the objective function formed as the sum of two terms, one has Lipschitz continuous gradient along…”
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On structural properties of Helbing's gas-kinetic traffic flow model by Necoara, I., De Schutter, B., Hellendoorn, H.

“…There exist several types of models that describe the evolution of traffic flow on freeways and urban roads. In this paper, we focus on some structural…”
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Parameter selection for best H moment matching-based model approximation through gradient optimization by Necoara, I., Ionescu, T. C.

“…In this paper we compute a family of reduced order models, parameterized in a matrix of free parameters, that match a prescribed set of \nu moments of a highly…”
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H2 model reduction of linear network systems by moment matching and optimization by Necoara, I, Ionescu, T. C

“…In this paper we study the problem of model reduction of linear network systems. We aim at computing a reduced order stable approximation of the network with…”
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Optimal H2 moment matching-based model reduction for linear systems by (non)convex optimization by Necoara, I, Ionescu, T. C

“…In this paper we compute families of reduced order models that match a prescribed set of moments of a highly dimensional linear time-invariant system. First,…”
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