Parallel Solution of Sparse Eigenproblems by Simultaneous Rayleigh Quotient Optimization with FSAI preconditioning. - Luca Bergamaschi; Angeles Martinez 001; Giorgio Pini (PARCO, 2003)

Eigenanalysis of Finite Element 3D Flow Models by Parallel Jacobi-Davidson. - Luca Bergamaschi; Angeles Martinez 001; Giorgio Pini; Flavio Sartoretto (PVM/MPI, 2003)

Parallel Acceleration of Krylov Solvers by Factorized Approximate Inverse Preconditioners. - Luca Bergamaschi; Angeles Martinez 001 (VECPAR, 2004)

A Parallel Exponential Integrator for Large-Scale Discretizations of Advection-Diffusion Models. - Luca Bergamaschi; Marco Caliari; Angeles Martinez 001; Marco Vianello (PVM/MPI, 2005)

Comparing Leja and Krylov Approximations of Large Scale Matrix Exponentials. - Luca Bergamaschi; Marco Caliari; Angeles Martinez 001; Marco Vianello (International Conference on Computational Science (4), 2006)

Parallel preconditioned conjugate gradient optimization of the Rayleigh quotient for the solution of sparse eigenproblems. - Luca Bergamaschi; Angeles Martinez 001; Giorgio Pini (Appl. Math. Comput., 2006)

A massively parallel exponential integrator for advection-diffusion models. - Angeles Martinez 001; Luca Bergamaschi; Marco Caliari; Marco Vianello (J. Comput. Appl. Math., 2009)

Parallel Inexact Constraint Preconditioners for Saddle Point Problems. - Luca Bergamaschi; Angeles Martinez 001 (Euro-Par (2), 2011)

FSAI-based parallel Mixed Constraint Preconditioners for saddle point problems arising in geomechanics. - Luca Bergamaschi; Angeles Martinez 001 (J. Comput. Appl. Math., 2011)

Low-rank update of preconditioners for the inexact Newton method with SPD Jacobian. - Luca Bergamaschi; Rafael Bru; Angeles Martinez 001 (Math. Comput. Model., 2011)

Quasi-Newton acceleration of ILU preconditioners for nonlinear two-phase flow equations in porous media. - Luca Bergamaschi; Rafael Bru; Angeles Martinez 001; Mario Putti (Adv. Eng. Softw., 2012)

Parallel Rayleigh Quotient Optimization with FSAI-Based Preconditioning. - Luca Bergamaschi; Angeles Martinez 001; Giorgio Pini (J. Appl. Math., 2012)

Banded target matrices and recursive FSAI for parallel preconditioning. - Luca Bergamaschi; Angeles Martinez 001 (Numer. Algorithms, 2012)

Parallel RFSAI-BFGS Preconditioners for Large Symmetric Eigenproblems. - Luca Bergamaschi; Angeles Martinez 001 (J. Appl. Math., 2013)

Low-rank update of preconditioners for the nonlinear Richards equation. - Luca Bergamaschi; Rafael Bru; Angeles Martinez 001; José Mas; Mario Putti (Math. Comput. Model., 2013)

Efficiently preconditioned inexact Newton methods for large symmetric eigenvalue problems. - Luca Bergamaschi; Angeles Martinez 001 (Optim. Methods Softw., 2015)

Tuned preconditioners for the eigensolution of large SPD matrices arising in engineering problems. - Angeles Martinez 001 (Numer. Linear Algebra Appl., 2016)

Spectral Acceleration of Parallel Iterative Eigensolvers for Large Scale Scientific Computing. - Luca Bergamaschi; Ángeles Martínez 001 (PARCO, 2017)

Two-stage spectral preconditioners for iterative eigensolvers. - Luca Bergamaschi; Angeles Martinez 001 (Numer. Linear Algebra Appl., 2017)

BFGS-like updates of constraint preconditioners for sequences of KKT linear systems in quadratic programming. - Luca Bergamaschi; Valentina De Simone; Daniela di Serafino; Ángeles Martínez 001 (Numer. Linear Algebra Appl., 2018)

Spectral preconditioners for the efficient numerical solution of a continuous branched transport model. - Luca Bergamaschi; Enrico Facca; Angeles Martinez 001; Mario Putti (J. Comput. Appl. Math., 2019)

Fast and stable rational RBF-based partition of unity interpolation. - Stefano De Marchi; Ángeles Martínez 001; Emma Perracchione (J. Comput. Appl. Math., 2019)

RBF-Based Partition of Unity Methods for Elliptic PDEs: Adaptivity and Stability Issues Via Variably Scaled Kernels. - Stefano De Marchi; Ángeles Martínez 001; Emma Perracchione; M. Rossini (J. Sci. Comput., 2019)

Compact Quasi-Newton preconditioners for SPD linear systems. - Luca Bergamaschi; José Marín; Angeles Martinez 001 (CoRR, 2020)

Compact quasi-Newton preconditioners for symmetric positive definite linear systems. - Luca Bergamaschi; José Marín; Ángeles Martínez 001 (Numer. Linear Algebra Appl., 2020)

Quadrature-based polynomial optimization. - Angeles Martinez 001; Federico Piazzon; Alvise Sommariva; Marco Vianello (Optim. Lett., 2020)

A new preconditioning approach for an interior point-proximal method of multipliers for linear and convex quadratic programming. - Luca Bergamaschi; Jacek Gondzio; Ángeles Martínez 001; John W. Pearson; Spyridon Pougkakiotis (Numer. Linear Algebra Appl., 2021)

Parallel Newton-Chebyshev polynomial preconditioners for the conjugate gradient method. - Luca Bergamaschi; Ángeles Martínez Calomardo (Comput. Math. Methods, 2021)

A Stochastic Modified Limited Memory BFGS for Training Deep Neural Networks. - Mahsa Yousefi; Ángeles Martínez Calomardo (SAI (2), 2022)

A stochastic nonmonotone trust-region training algorithm for image classification. - Mahsa Yousefi; Ángeles Martínez Calomardo (SITIS, 2022)

On the efficiency of Stochastic Quasi-Newton Methods for Deep Learning. - Mahsa Yousefi; Angeles Martinez 001 (CoRR, 2022)

Strategies of Preconditioner Updates for Sequences of Linear Systems Associated with the Neutron Diffusion. - Amanda Carreño; Luca Bergamaschi; Angeles Martinez 001; Damián Ginestar; Antoni Vidal-Ferràndiz; Gumersindo Verdú (Comput. Math. Methods, 2022)

Combined First- and Second-Order Directions for Deep Neural Networks Training. - Ángeles Martínez 001; Marco Viola; Mahsa Yousefi (NUMTA (1), 2023)

Deep Neural Networks Training by Stochastic Quasi-Newton Trust-Region Methods. - Mahsa Yousefi; Angeles Martinez 001 (Algorithms, 2023)

Fast Iterative Solver for the All-at-Once Runge-Kutta Discretization. - Santolo Leveque; Luca Bergamaschi; Ángeles Martínez 001; John W. Pearson (CoRR, 2023)

Parallel matrix-free polynomial preconditioners with application to flow simulations in discrete fracture networks. - Luca Bergamaschi; Massimiliano Ferronato; Giovanni Isotton; Carlo Janna; Angeles Martinez 001 (Comput. Math. Appl., 2023)

Parallel-in-Time Solver for the All-at-Once Runge-Kutta Discretization. - Santolo Leveque; Luca Bergamaschi; Ángeles Martínez 001; John W. Pearson (SIAM J. Matrix Anal. Appl., 2024)

Some preconditioning techniques for a class of double saddle point problems. - Fariba Balani Bakrani; Luca Bergamaschi; Ángeles Martínez 001; Masoud Hajarian (Numer. Linear Algebra Appl., 2024)

A non-monotone trust-region method with noisy oracles and additional sampling. - Natasa Krejic; Natasa Krklec Jerinkic; Angeles Martinez 001; Mahsa Yousefi (Comput. Optim. Appl., 2024)

Triangular preconditioners for double saddle point linear systems arising in the mixed form of poroelasticity equations. - Luca Bergamaschi; Massimiliano Ferronato; Angeles Martinez 001 (CoRR, 2025)

Spectral analysis of block preconditioners for double saddle-point linear systems with application to PDE-constrained optimization. - Luca Bergamaschi; Ángeles Martínez 001; John W. Pearson; Andreas Potschka (Comput. Optim. Appl., 2025)

Eigenvalue bounds for preconditioned symmetric multiple saddle-point matrices. - Luca Bergamaschi; Angeles Martinez 001; John W. Pearson; Andreas Potschka (CoRR, 2025)