Pubblicazioni di Caliciotti Andrea

2021

Ricciardi Celsi Lorenzo, Caliciotti Andrea, D'Onorio Matteo, Scocchi Eugenio, Sulieman Nour Alhuda, Villari Massimo

On Predicting Ticket Reopening for Improving Customer Service in 5G Fiber Optic Networks. FUTURE INTERNET 2021: 1-16

2020

Al-Baali Mehiddin, Caliciotti Andrea, Fasano Giovanni, Roma Massimo

A Class of Approximate Inverse Preconditioners Based on Krylov-Subspace Methods for Large-Scale Nonconvex Optimization. SIAM JOURNAL ON OPTIMIZATION 2020: 1954-1979

Caliciotti Andrea, Fasano Giovanni, Potra Florian, Roma Massimo

Issues on the use of a modified Bunch and Kaufman decomposition for large scale Newton’s equation. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2020: -

Caliciotti A., Ricciardi Celsi

On Optimal Buffer Allocation for Guaranteeing Quality of Service in Multimedia Internet Broadcasting for Mobile Networks. INTERNATIONAL JOURNAL OF CONTROL, AUTOMATION, AND SYSTEMS 2020: -

2018-02-19

Caliciotti Andrea

Advances in large scale unconstrained optimization: novel preconditioning strategies for Nonlinear Conjugate Gradient methods and new developments in Newton-Krylov methods. 2018-02-19: -

2018

Caliciotti Andrea, Fasano Giovanni, Nash Stephen G., Roma Massimo

An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization. OPERATIONS RESEARCH LETTERS 2018: 7-12

Caliciotti Andrea, Fasano Giovanni, Nash S. G., Roma Massimo

Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods in large scale nonconvex optimization. DATA IN BRIEF 2018: 246-255

Caliciotti Andrea, Fasano Giovanni, Roma Massimo

Preconditioned nonlinear conjugate gradient methods based on a modified secant equation. APPLIED MATHEMATICS AND COMPUTATION 2018: 196-214

Al-Baali Mehiddin, Caliciotti Andrea, Fasano Giovanni, Roma Massimo

Quasi-Newton based preconditioning and damped quasi-Newton schemes for nonlinear conjugate gradient methods. Numerical analysis and optimization 2018: 1-21

2017

Al Baali M, Caliciotti Andrea, Fasano Giovanni, Roma Massimo

Exploiting damped techniques for nonlinear conjugate gradient methods. MATHEMATICAL METHODS OF OPERATIONS RESEARCH 2017: 501-522

Caliciotti Andrea, Giovanni Fasano, Roma Massimo

Novel preconditioners based on quasi–Newton updates for nonlinear conjugate gradient methods. OPTIMIZATION LETTERS 2017: 835-853

2016

Caliciotti Andrea, Fasano Giovanni, Roma Massimo

Preconditioning strategies for nonlinear conjugate gradient methods, based on quasi-Newton updates. Numerical computations: theory and algorithms (NUMTA–2016). Proceedings of the 2nd international conference “Numerical computations: theory and agorithms” 2016: -