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ORCIDAngeles Martinez 0001
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- affiliation: University of Trieste, Department of Mathematics and Geosciences, Italy
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Journal Articles
- 2023
[j23]Mahsa Yousefi
, Angeles Martinez:
Deep Neural Networks Training by Stochastic Quasi-Newton Trust-Region Methods. Algorithms 16(10): 490 (2023)- [j22]Luca Bergamaschi, Massimiliano Ferronato, Giovanni Isotton, Carlo Janna, Angeles Martinez:
Parallel matrix-free polynomial preconditioners with application to flow simulations in discrete fracture networks. Comput. Math. Appl. 146: 60-70 (2023) - 2022
- [j21]Amanda Carreño, Luca Bergamaschi, Angeles Martinez, Damián Ginestar, Antoni Vidal-Ferràndiz, Gumersindo Verdú:
Strategies of Preconditioner Updates for Sequences of Linear Systems Associated with the Neutron Diffusion. Comput. Math. Methods 2022: 1-13 (2022) - 2021
- [j20]Luca Bergamaschi, Ángeles Martínez Calomardo:
Parallel Newton-Chebyshev polynomial preconditioners for the conjugate gradient method. Comput. Math. Methods 3(6) (2021) - [j19]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) - 2020
- [j18]Luca Bergamaschi, José Marín, Ángeles Martínez:
Compact quasi-Newton preconditioners for symmetric positive definite linear systems. Numer. Linear Algebra Appl. 27(6) (2020) - [j17]Angeles Martinez, Federico Piazzon, Alvise Sommariva, Marco Vianello:
Quadrature-based polynomial optimization. Optim. Lett. 14(5): 1027-1036 (2020) - 2019
- [j16]Stefano De Marchi, Ángeles Martínez, Emma Perracchione:
Fast and stable rational RBF-based partition of unity interpolation. J. Comput. Appl. Math. 349: 331-343 (2019) - [j15]Luca Bergamaschi, Enrico Facca, Angeles Martinez, Mario Putti:
Spectral preconditioners for the efficient numerical solution of a continuous branched transport model. J. Comput. Appl. Math. 354: 259-270 (2019) - [j14]Stefano De Marchi, Ángeles Martínez, Emma Perracchione, M. Rossini:
RBF-Based Partition of Unity Methods for Elliptic PDEs: Adaptivity and Stability Issues Via Variably Scaled Kernels. J. Sci. Comput. 79(1): 321-344 (2019) - 2018
- [j13]Luca Bergamaschi, Valentina De Simone, Daniela di Serafino, Ángeles Martínez:
BFGS-like updates of constraint preconditioners for sequences of KKT linear systems in quadratic programming. Numer. Linear Algebra Appl. 25(5) (2018) - 2017
- [j12]Luca Bergamaschi, Angeles Martinez:
Two-stage spectral preconditioners for iterative eigensolvers. Numer. Linear Algebra Appl. 24(3) (2017) - 2016
- [j11]Angeles Martinez:
Tuned preconditioners for the eigensolution of large SPD matrices arising in engineering problems. Numer. Linear Algebra Appl. 23(3): 427-443 (2016) - 2015
- [j10]Luca Bergamaschi, Angeles Martinez:
Efficiently preconditioned inexact Newton methods for large symmetric eigenvalue problems. Optim. Methods Softw. 30(2): 301-322 (2015) - 2013
- [j9]Luca Bergamaschi, Angeles Martinez:
Parallel RFSAI-BFGS Preconditioners for Large Symmetric Eigenproblems. J. Appl. Math. 2013: 767042:1-767042:10 (2013) - [j8]Luca Bergamaschi, Rafael Bru, Angeles Martinez, José Mas, Mario Putti:
Low-rank update of preconditioners for the nonlinear Richards equation. Math. Comput. Model. 57(7-8): 1933-1941 (2013) - 2012
- [j7]Luca Bergamaschi, Rafael Bru, Angeles Martinez, Mario Putti:
Quasi-Newton acceleration of ILU preconditioners for nonlinear two-phase flow equations in porous media. Adv. Eng. Softw. 46(1): 63-68 (2012) - [j6]Luca Bergamaschi, Angeles Martinez, Giorgio Pini:
Parallel Rayleigh Quotient Optimization with FSAI-Based Preconditioning. J. Appl. Math. 2012: 872901:1-872901:14 (2012) - [j5]Luca Bergamaschi, Angeles Martinez:
Banded target matrices and recursive FSAI for parallel preconditioning. Numer. Algorithms 61(2): 223-241 (2012) - 2011
- [j4]Luca Bergamaschi, Angeles Martinez:
FSAI-based parallel Mixed Constraint Preconditioners for saddle point problems arising in geomechanics. J. Comput. Appl. Math. 236(3): 308-318 (2011) - [j3]Luca Bergamaschi, Rafael Bru, Angeles Martinez:
Low-rank update of preconditioners for the inexact Newton method with SPD Jacobian. Math. Comput. Model. 54(7-8): 1863-1873 (2011) - 2009
- [j2]Angeles Martinez, Luca Bergamaschi, Marco Caliari, Marco Vianello:
A massively parallel exponential integrator for advection-diffusion models. J. Comput. Appl. Math. 231(1): 82-91 (2009) - 2006
- [j1]Luca Bergamaschi, Angeles Martinez, Giorgio Pini:
Parallel preconditioned conjugate gradient optimization of the Rayleigh quotient for the solution of sparse eigenproblems. Appl. Math. Comput. 175(2): 1694-1715 (2006)
Conference and Workshop Papers
- 2022
- [c9]Mahsa Yousefi, Ángeles Martínez Calomardo:
A Stochastic Modified Limited Memory BFGS for Training Deep Neural Networks. SAI (2) 2022: 9-28 - [c8]Mahsa Yousefi, Ángeles Martínez Calomardo:
A stochastic nonmonotone trust-region training algorithm for image classification. SITIS 2022: 522-529 - 2017
- [c7]Luca Bergamaschi, Ángeles Martínez:
Spectral Acceleration of Parallel Iterative Eigensolvers for Large Scale Scientific Computing. PARCO 2017: 107-116 - 2011
- [c6]Luca Bergamaschi, Angeles Martinez:
Parallel Inexact Constraint Preconditioners for Saddle Point Problems. Euro-Par (2) 2011: 78-89 - 2006
- [c5]Luca Bergamaschi, Marco Caliari, Angeles Martinez, Marco Vianello:
Comparing Leja and Krylov Approximations of Large Scale Matrix Exponentials. International Conference on Computational Science (4) 2006: 685-692 - 2005
- [c4]Luca Bergamaschi, Marco Caliari, Angeles Martinez, Marco Vianello:
A Parallel Exponential Integrator for Large-Scale Discretizations of Advection-Diffusion Models. PVM/MPI 2005: 483-492 - 2004
- [c3]Luca Bergamaschi, Angeles Martinez:
Parallel Acceleration of Krylov Solvers by Factorized Approximate Inverse Preconditioners. VECPAR 2004: 623-636 - 2003
- [c2]Luca Bergamaschi, Angeles Martinez, Giorgio Pini:
Parallel Solution of Sparse Eigenproblems by Simultaneous Rayleigh Quotient Optimization with FSAI preconditioning. PARCO 2003: 275-282 - [c1]Luca Bergamaschi, Angeles Martinez, Giorgio Pini, Flavio Sartoretto:
Eigenanalysis of Finite Element 3D Flow Models by Parallel Jacobi-Davidson. PVM/MPI 2003: 565-569
Informal and Other Publications
- 2024
- [i8]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) - 2023
- [i7]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) - [i6]Fariba Bakrani Balani, Luca Bergamaschi, Angeles Martinez, Masoud Hajarian:
Some preconditioning techniques for a class of double saddle point problems. CoRR abs/2307.00525 (2023) - 2022
- [i5]Mahsa Yousefi, Angeles Martinez:
On the efficiency of Stochastic Quasi-Newton Methods for Deep Learning. CoRR abs/2205.09121 (2022) - [i4]Luca Bergamaschi, Massimiliano Ferronato, Giovanni Isotton, Carlo Janna, Angeles Martinez:
Parallel Matrix-free polynomial preconditioners with application to flow simulations in discrete fracture networks. CoRR abs/2208.01339 (2022) - 2020
- [i3]Luca Bergamaschi, José Marín, Angeles Martinez:
Compact Quasi-Newton preconditioners for SPD linear systems. CoRR abs/2001.01062 (2020) - [i2]Luca Bergamaschi, Angeles Martinez:
Parallel Newton-Chebyshev Polynomial Preconditioners for the Conjugate Gradient method. CoRR abs/2008.01440 (2020) - 2019
- [i1]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)
Coauthor Index
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