Search results for "Computer Science - Numerical Analysis"

showing 4 items of 4 documents

Guaranteed error control bounds for the stabilised space-time IgA approximations to parabolic problems

2017

The paper is concerned with space-time IgA approximations of parabolic initial-boundary value problems. We deduce guaranteed and fully computable error bounds adapted to special features of IgA approximations and investigate their applicability. The derivation method is based on the analysis of respective integral identities and purely functional arguments. Therefore, the estimates do not contain mesh-dependent constants and are valid for any approximation from the admissible (energy) class. In particular, they provide computable error bounds for norms associated with stabilised space-time IgA approximations as well as imply efficient error indicators enhancing the performance of fully adap…

65N15 65N25 65N35F.2.1; G.1.0; G.1.2; G.1.3; G.1.8; B.2.3Computer Science - Numerical AnalysisG.1.8B.2.3FOS: MathematicsG.1.2Mathematics - Numerical AnalysisF.2.1G.1.3Numerical Analysis (math.NA)G.1.0
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Randomized Block Frank–Wolfe for Convergent Large-Scale Learning

2017

Owing to their low-complexity iterations, Frank-Wolfe (FW) solvers are well suited for various large-scale learning tasks. When block-separable constraints are present, randomized block FW (RB-FW) has been shown to further reduce complexity by updating only a fraction of coordinate blocks per iteration. To circumvent the limitations of existing methods, the present work develops step sizes for RB-FW that enable a flexible selection of the number of blocks to update per iteration while ensuring convergence and feasibility of the iterates. To this end, convergence rates of RB-FW are established through computational bounds on a primal sub-optimality measure and on the duality gap. The novel b…

FOS: Computer and information sciencesMathematical optimization0102 computer and information sciences02 engineering and technology01 natural sciencesMeasure (mathematics)Machine Learning (cs.LG)Convergence (routing)FOS: Mathematics0202 electrical engineering electronic engineering information engineeringFraction (mathematics)Electrical and Electronic EngineeringMathematics - Optimization and ControlMathematicsSequenceDuality gapComputer Science - Numerical Analysis020206 networking & telecommunicationsNumerical Analysis (math.NA)Stationary pointSupport vector machineComputer Science - LearningOptimization and Control (math.OC)010201 computation theory & mathematicsIterated functionSignal ProcessingAlgorithmIEEE Transactions on Signal Processing
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NUMERICAL ALGORITHMS

2013

For many systems of differential equations modeling problems in science and engineering, there are natural splittings of the right hand side into two parts, one non-stiff or mildly stiff, and the other one stiff. For such systems implicit-explicit (IMEX) integration combines an explicit scheme for the non-stiff part with an implicit scheme for the stiff part. In a recent series of papers two of the authors (Sandu and Zhang) have developed IMEX GLMs, a family of implicit-explicit schemes based on general linear methods. It has been shown that, due to their high stage order, IMEX GLMs require no additional coupling order conditions, and are not marred by order reduction. This work develops a …

General linear methodsMathematical optimizationIMEX methods; general linear methods; error analysis; order conditions; stability analysisIMEX methodsDifferential equationSCHEMESorder conditionsMathematics AppliedExtrapolationStability (learning theory)QUADRATIC STABILITYstability analysisPARABOLIC EQUATIONSSYSTEMSNORDSIECK METHODSFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisRUNGE-KUTTA METHODSMULTISTEP METHODSerror analysisMathematicsCONSTRUCTIONSeries (mathematics)Applied MathematicsNumerical analysisComputer Science - Numerical AnalysisStability analysisORDEROrder conditionsNumerical Analysis (math.NA)Computer Science::Numerical AnalysisRunge–Kutta methodsGeneral linear methodsError analysisORDINARY DIFFERENTIAL-EQUATIONSOrdinary differential equationgeneral linear methodsMathematics
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On the a posteriori error analysis for linear Fokker-Planck models in convection-dominated diffusion problems

2018

This work is aimed at the derivation of reliable and efficient a posteriori error estimates for convection-dominated diffusion problems motivated by a linear Fokker-Planck problem appearing in computational neuroscience. We obtain computable error bounds of the functional type for the static and time-dependent case and for different boundary conditions (mixed and pure Neumann boundary conditions). Finally, we present a set of various numerical examples including discussions on mesh adaptivity and space-time discretisation. The numerical results confirm the reliability and efficiency of the error estimates derived.

Work (thermodynamics)Discretizationelliptic partial differential equations01 natural sciencesdiffuusiodiffuusio (fysikaaliset ilmiöt)mesh-adaptivityFOS: MathematicsNeumann boundary conditionApplied mathematicsBoundary value problemMathematics - Numerical Analysis0101 mathematicsDiffusion (business)virheanalyysiMathematicsosittaisdifferentiaaliyhtälötconvection-dominated diffusion problemsApplied Mathematicsta111010102 general mathematicsComputer Science - Numerical AnalysisNumerical Analysis (math.NA)a posteriori error estimation010101 applied mathematicsparabolic partial differential equationsComputational MathematicsElliptic partial differential equationA priori and a posterioriFokker–Planck equation
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