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ORCIDJohn W. Pearson
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2020 – today
- 2024
[j23]John W. Pearson
, Andreas Potschka:
Double saddle-point preconditioning for Krylov methods in the inexact sequential homotopy method. Numer. Linear Algebra Appl. 31(4) (2024)- [j22]Santolo Leveque, Luca Bergamaschi, Ángeles Martínez, John W. Pearson:
Parallel-in-Time Solver for the All-at-Once Runge-Kutta Discretization. SIAM J. Matrix Anal. Appl. 45(4): 1902-1928 (2024) - [i18]Luca Bergamaschi, Angeles Martinez, John W. Pearson, Andreas Potschka:
Spectral analysis of block preconditioners for double saddle-point linear systems with application to PDE-constrained optimization. CoRR abs/2405.14605 (2024) - [i17]Bernhard Heinzelreiter, John W. Pearson:
Diagonalization-Based Parallel-in-Time Preconditioners for Instationary Fluid Flow Control Problems. CoRR abs/2405.18964 (2024) - [i16]Andrés Miniguano-Trujillo, John W. Pearson, Benjamin D. Goddard:
Efficient nonlocal linear image denoising: Bilevel optimization with Nonequispaced Fast Fourier Transform and matrix-free preconditioning. CoRR abs/2407.06834 (2024) - [i15]Karolína Benková, John W. Pearson, Mariya Ptashnyk:
Fast numerical solvers for parameter identification problems in mathematical biology. CoRR abs/2408.14926 (2024) - [i14]Santolo Leveque, James R. Maddison, John W. Pearson:
Automatic Differentiation for All-at-once Systems Arising in Certain PDE-Constrained Optimization Problems. CoRR abs/2408.17312 (2024) - [i13]Christoph Hansknecht, Bernhard Heinzelreiter, John W. Pearson, Andreas Potschka:
A Framework for the Solution of Tree-Coupled Saddle-Point Systems. CoRR abs/2410.23385 (2024) - 2023
- [i12]Santolo Leveque, Luca Bergamaschi, Ángeles Martínez, John W. Pearson:
Fast Iterative Solver for the All-at-Once Runge-Kutta Discretization. CoRR abs/2303.02090 (2023) - [i11]Theresa Wagner, John W. Pearson, Martin Stoll:
A Preconditioned Interior Point Method for Support Vector Machines Using an ANOVA-Decomposition and NFFT-Based Matrix-Vector Products. CoRR abs/2312.00538 (2023) - 2022
- [j21]Jacek Gondzio, Spyridon Pougkakiotis, John W. Pearson:
General-purpose preconditioning for regularized interior point methods. Comput. Optim. Appl. 83(3): 727-757 (2022) - [j20]Santolo Leveque, John W. Pearson:
Fast iterative solver for the optimal control of time-dependent PDEs with Crank-Nicolson discretization in time. Numer. Linear Algebra Appl. 29(2) (2022) - [j19]Santolo Leveque, John W. Pearson:
Parameter-Robust Preconditioning for Oseen Iteration Applied to Stationary and Instationary Navier-Stokes Control. SIAM J. Sci. Comput. 44(3): 694- (2022) - [i10]Jonna C. Roden, Rory D. Mills-Williams, John W. Pearson, Benjamin D. Goddard:
MultiShape: A Spectral Element Method, with Applications to Dynamic Density Functional Theory and PDE-Constrained Optimization. CoRR abs/2207.05589 (2022) - 2021
- [j18]Luca Bergamaschi, Jacek Gondzio, Ángeles Martínez, John W. Pearson, Spyridon Pougkakiotis:
A new preconditioning approach for an interior point-proximal method of multipliers for linear and convex quadratic programming. Numer. Linear Algebra Appl. 28(4) (2021) - [i9]Jemima M. Tabeart, John W. Pearson:
Saddle point preconditioners for weak-constraint 4D-Var. CoRR abs/2105.06975 (2021) - [i8]John W. Pearson, Andreas Potschka:
A Note On Symmetric Positive Definite Preconditioners for Multiple Saddle-Point Systems. CoRR abs/2106.12433 (2021) - [i7]Jacek Gondzio, Spyridon Pougkakiotis, John W. Pearson:
General-purpose preconditioning for regularized interior point methods. CoRR abs/2107.06822 (2021) - [i6]Santolo Leveque, John W. Pearson:
Parameter-Robust Preconditioning for Oseen Iteration Applied to Stationary and Instationary Navier-Stokes Control. CoRR abs/2108.00282 (2021) - [i5]John W. Pearson, Andreas Potschka:
A Preconditioned Inexact Active-Set Method for Large-Scale Nonlinear Optimal Control Problems. CoRR abs/2112.05020 (2021) - 2020
- [j17]Jun Liu, John W. Pearson:
Parameter-robust preconditioning for the optimal control of the wave equation. Numer. Algorithms 83(3): 1171-1203 (2020) - [j16]John W. Pearson, Margherita Porcelli, Martin Stoll:
Interior-point methods and preconditioning for PDE-constrained optimization problems involving sparsity terms. Numer. Linear Algebra Appl. 27(2) (2020) - [j15]Spyridon Pougkakiotis, John W. Pearson, Santolo Leveque, Jacek Gondzio:
Fast Solution Methods for Convex Quadratic Optimization of Fractional Differential Equations. SIAM J. Matrix Anal. Appl. 41(3): 1443-1476 (2020) - [i4]Santolo Leveque, John W. Pearson:
Fast Iterative Solver for the Optimal Control of Time-Dependent PDEs with Crank-Nicolson Discretization in Time. CoRR abs/2007.08410 (2020) - [i3]Mildred Aduamoah, Benjamin D. Goddard, John W. Pearson, Jonna C. Roden:
PDE-Constrained Optimization Models and Pseudospectral Methods for Multiscale Particle Dynamics. CoRR abs/2009.09850 (2020)
2010 – 2019
- 2019
- [j14]Roland Herzog, John W. Pearson, Martin Stoll:
Fast iterative solvers for an optimal transport problem. Adv. Comput. Math. 45(2): 495-517 (2019) - [j13]Sergey Dolgov, John W. Pearson:
Preconditioners and Tensor Product Solvers for Optimal Control Problems from Chemotaxis. SIAM J. Sci. Comput. 41(6): B1228-B1253 (2019) - [i2]Luca Bergamaschi, Jacek Gondzio, Ángeles Martínez, John W. Pearson, Spyridon Pougkakiotis:
A New Preconditioning Approach for an Interior Point-Proximal Method of Multipliers for Linear and Convex Quadratic Programming. CoRR abs/1912.10064 (2019) - 2018
- [j12]John W. Pearson, Jennifer Pestana, David J. Silvester:
Refined saddle-point preconditioners for discretized Stokes problems. Numerische Mathematik 138(2): 331-363 (2018) - 2017
- [j11]John W. Pearson, Sheehan Olver, Mason A. Porter:
Numerical methods for the computation of the confluent and Gauss hypergeometric functions. Numer. Algorithms 74(3): 821-866 (2017) - [j10]John W. Pearson, Jacek Gondzio:
Fast interior point solution of quadratic programming problems arising from PDE-constrained optimization. Numerische Mathematik 137(4): 959-999 (2017) - [j9]Patrick E. Farrell, John W. Pearson:
A Preconditioner for the Ohta-Kawasaki Equation. SIAM J. Matrix Anal. Appl. 38(1): 217-225 (2017) - 2016
- [j8]Sergey Dolgov, John W. Pearson, Dmitry V. Savostyanov, Martin Stoll:
Fast tensor product solvers for optimization problems with fractional differential equations as constraints. Appl. Math. Comput. 273: 604-623 (2016) - [j7]Martin Stoll, John W. Pearson, Philip K. Maini:
Fast solvers for optimal control problems from pattern formation. J. Comput. Phys. 304: 27-45 (2016) - 2015
- [j6]John W. Pearson:
Preconditioned iterative methods for Navier-Stokes control problems. J. Comput. Phys. 292: 194-207 (2015) - 2014
- [j5]John W. Pearson, Martin Stoll, Andrew J. Wathen:
Preconditioners for state-constrained optimal control problems with Moreau-Yosida penalty function. Numer. Linear Algebra Appl. 21(1): 81-97 (2014) - [i1]John W. Pearson, Sheehan Olver, Mason A. Porter:
Numerical Methods for the Computation of the Confluent and Gauss Hypergeometric Functions. CoRR abs/1407.7786 (2014) - 2013
- [j4]John W. Pearson:
A radial basis function method for solving PDE-constrained optimization problems. Numer. Algorithms 64(3): 481-506 (2013) - [j3]John W. Pearson, Martin Stoll:
Fast Iterative Solution of Reaction-Diffusion Control Problems Arising from Chemical Processes. SIAM J. Sci. Comput. 35(5) (2013) - 2012
- [j2]John W. Pearson, Andrew J. Wathen:
A new approximation of the Schur complement in preconditioners for PDE-constrained optimization. Numer. Linear Algebra Appl. 19(5): 816-829 (2012) - [j1]John W. Pearson, Martin Stoll, Andrew J. Wathen:
Regularization-Robust Preconditioners for Time-Dependent PDE-Constrained Optimization Problems. SIAM J. Matrix Anal. Appl. 33(4): 1126-1152 (2012)
Coauthor Index
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