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Publications

by alumni of

"Sapienza" Università di Roma → Facoltà di Ingegneria dell'Informazione Informatica e Statistica → Dipartimento di Ingegneria Informatica, Automatica e Gestionale "Antonio Ruberti"

Sapienza University of Rome → Faculty of Computer and Statistical Information Engineering → Department of Computer, Control and Management Engineering

These are publications listed in RePEc written by alumni of the above institution who are registered with the RePEc Author Service and listed in the RePEc Genealogy. List of alumni. For a list of publications by current members of the department, see here. Register yourself.

This page is updated in the first days of each month.

| Working papers | Journal articles | Chapters |

Working papers

2022

  1. Giovanni Fasano & Christian Piermarini & Massimo Roma, 2022, "Bridging the gap between Trust–Region Methods (TRMs) and Linesearch Based Methods (LBMs) for Nonlinear Programming: quadratic sub–problems," Working Papers, Venice School of Management - Department of Management, Università Ca' Foscari Venezia, number 08, Jul.

2021

  1. Andrea Pontiggia & Giovanni Fasano, 2021, "Data Analytics and Machine Learning paradigm to gauge performances combining classification, ranking and sorting for system analysis," Working Papers, Venice School of Management - Department of Management, Università Ca' Foscari Venezia, number 05, Jul.
  2. Valentina Aprigliano & Simone Emiliozzi & Gabriele Guaitoli & Andrea Luciani & Juri Marcucci & Libero Monteforte, 2021, "The power of text-based indicators in forecasting the Italian economic activity," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1321, Mar.

2020

  1. Michele Loberto & Andrea Luciani & Marco Pangallo, 2020, "What do online listings tell us about the housing market?," Papers, arXiv.org, number 2004.02706, Apr.

2019

  1. Marco Corazza & Giovanni Fasano & Riccardo Gusso & Raffaele Pesenti, 2019, "A comparison among Reinforcement Learning algorithms in financial trading systems," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2019:33.
  2. Marco Corazza & Giovanni Fasano & Daniela Favaretto & Silvio Giove, 2019, "Properties of some generalized means for positive sequences," Working Papers, Venice School of Management - Department of Management, Università Ca' Foscari Venezia, number 05, Dec.

2018

  1. Michele Loberto & Andrea Luciani & Marco Pangallo, 2018, "The potential of big housing data: an application to the Italian real-estate market," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1171, Apr.

2017

  1. Mehiddin Al-Baali & Andrea Caliciotti & Giovanni Fasano & Massimo Roma, 2017, "Exploiting damped techniques for nonlinear conjugate gradient methods," DIAG Technical Reports, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza", number 2017-05.
  2. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2017, "PSO-based tuning of MURAME parameters for creditworthiness evaluation of Italian SMEs," Working Papers, Venice School of Management - Department of Management, Università Ca' Foscari Venezia, number 04, Apr.

2015

  1. Giovanni Fasano & Massimo Roma, 2015, "An estimation of the condition number for a class of indefinite preconditioned matrices," DIAG Technical Reports, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza", number 2015-01.
  2. Marco Corazza & Giacomo Di Tollo & Giovanni Fasano & Raffaele Pesenti, 2015, "A novel initialization of PSO for costly portfolio selection problems," Working Papers, Venice School of Management - Department of Management, Università Ca' Foscari Venezia, number 4, Jul.

2014

  1. Giovanni Fasano, 2014, "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers, arXiv.org, number 1408.6043, Aug.

2013

  1. E.F. Campana & Matteo Diez & Giovanni Fasano & Daniele Peri, 2013, "Initial particles position for PSO, in Bound Constrained Optimization," Working Papers, Venice School of Management - Department of Management, Università Ca' Foscari Venezia, number 6, Jun.

2011

  1. Marco Corazza & Giovanni Fasano & Riccardo Gusso, 2011, "Particle Swarm Optimization with non-smooth penalty reformulation for a complex portfolio selection problem," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2011_10.
  2. Giovanni Fasano & Massimo Roma, 2011, "A class of preconditioners for large indefinite linear systems, as byproduct of Krylov subspace methods: Part I," Working Papers, Venice School of Management - Department of Management, Università Ca' Foscari Venezia, number 4, Jun.

2008

  1. Giovanni Fasano, 2008, "Notes on a 3-term Conjugacy Recurrence for the Iterative Solution of Symmetric Linear Systems," Working Papers, Department of Applied Mathematics, Università Ca' Foscari Venezia, number 179, Nov.
  2. Andrea Ellero & Giovanni Fasano & Annamaria Sorato, 2008, "A Modified Galam's Model," Working Papers, Department of Applied Mathematics, Università Ca' Foscari Venezia, number 180, Nov.

Journal articles

2025

  1. Giovanni Fasano & Christian Piermarini & Massimo Roma, 2025, "Exploiting effective negative curvature directions via SYMMBK algorithm, in Newton–Krylov methods," Computational Optimization and Applications, Springer, volume 91, issue 2, pages 617-647, June, DOI: 10.1007/s10589-025-00650-7.

2024

  1. Andrea Caliciotti & Marco Corazza & Giovanni Fasano, 2024, "From regression models to machine learning approaches for long term Bitcoin price forecast," Annals of Operations Research, Springer, volume 336, issue 1, pages 359-381, May, DOI: 10.1007/s10479-023-05444-w.

2023

  1. Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023, "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, volume 39, issue 2, pages 791-808, DOI: 10.1016/j.ijforecast.2022.02.006.

2022

  1. Michele Loberto & Andrea Luciani & Marco Pangallo, 2022, "What Do Online Listings Tell Us about the Housing Market?," International Journal of Central Banking, International Journal of Central Banking, volume 18, issue 4, pages 1-52, October.

2021

  1. Marco Corazza & Giacomo di Tollo & Giovanni Fasano & Raffaele Pesenti, 2021, "A novel hybrid PSO-based metaheuristic for costly portfolio selection problems," Annals of Operations Research, Springer, volume 304, issue 1, pages 109-137, September, DOI: 10.1007/s10479-021-04075-3.
  2. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2021, "MURAME parameter setting for creditworthiness evaluation: data-driven optimization," Decisions in Economics and Finance, Springer;Associazione per la Matematica, volume 44, issue 1, pages 295-339, June, DOI: 10.1007/s10203-021-00322-1.

2020

  1. Andrea Caliciotti & Giovanni Fasano & Florian Potra & Massimo Roma, 2020, "Issues on the use of a modified Bunch and Kaufman decomposition for large scale Newton’s equation," Computational Optimization and Applications, Springer, volume 77, issue 3, pages 627-651, December, DOI: 10.1007/s10589-020-00225-8.
  2. Renato Leone & Giovanni Fasano & Massimo Roma & Yaroslav D. Sergeyev, 2020, "Iterative Grossone-Based Computation of Negative Curvature Directions in Large-Scale Optimization," Journal of Optimization Theory and Applications, Springer, volume 186, issue 2, pages 554-589, August, DOI: 10.1007/s10957-020-01717-7.

2018

  1. Caliciotti, Andrea & Fasano, Giovanni & Roma, Massimo, 2018, "Preconditioned Nonlinear Conjugate Gradient methods based on a modified secant equation," Applied Mathematics and Computation, Elsevier, volume 318, issue C, pages 196-214, DOI: 10.1016/j.amc.2017.08.029.
  2. Renato De Leone & Giovanni Fasano & Yaroslav D. Sergeyev, 2018, "Planar methods and grossone for the Conjugate Gradient breakdown in nonlinear programming," Computational Optimization and Applications, Springer, volume 71, issue 1, pages 73-93, September, DOI: 10.1007/s10589-017-9957-y.

2017

  1. Giovanni Fasano & Raffaele Pesenti, 2017, "Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces," Journal of Optimization Theory and Applications, Springer, volume 175, issue 3, pages 764-794, December, DOI: 10.1007/s10957-017-1180-6.
  2. Mehiddin Al-Baali & Andrea Caliciotti & Giovanni Fasano & Massimo Roma, 2017, "Exploiting damped techniques for nonlinear conjugate gradient methods," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), volume 86, issue 3, pages 501-522, December, DOI: 10.1007/s00186-017-0593-1.

2016

  1. Giovanni Fasano & Massimo Roma, 2016, "A novel class of approximate inverse preconditioners for large positive definite linear systems in optimization," Computational Optimization and Applications, Springer, volume 65, issue 2, pages 399-429, November, DOI: 10.1007/s10589-015-9765-1.

2015

  1. Giovanni Fasano, 2015, "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, volume 164, issue 3, pages 883-914, March, DOI: 10.1007/s10957-014-0600-0.

2013

  1. Giovanni Fasano & Massimo Roma, 2013, "Preconditioning Newton–Krylov methods in nonconvex large scale optimization," Computational Optimization and Applications, Springer, volume 56, issue 2, pages 253-290, October, DOI: 10.1007/s10589-013-9563-6.

2012

  1. Emilio Fortunato Campana & Giovanni Fasano & Daniele Peri, 2012, "Penalty function approaches for ship multidisciplinary design optimisation (MDO)," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, volume 6, issue 6, pages 765-784.

2009

  1. Ellero, Andrea & Fasano, Giovanni & Sorato, Annamaria, 2009, "A modified Galam’s model for word-of-mouth information exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 388, issue 18, pages 3901-3910, DOI: 10.1016/j.physa.2009.06.002.

2007

  1. G. Fasano, 2007, "Lanczos Conjugate-Gradient Method and Pseudoinverse Computation on Indefinite and Singular Systems," Journal of Optimization Theory and Applications, Springer, volume 132, issue 2, pages 267-285, February, DOI: 10.1007/s10957-006-9119-3.

2005

  1. G. Fasano, 2005, "Planar Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization, Part 1: Theory," Journal of Optimization Theory and Applications, Springer, volume 125, issue 3, pages 523-541, June, DOI: 10.1007/s10957-005-2087-1.
  2. G. Fasano, 2005, "Planar Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization, Part 2: Application," Journal of Optimization Theory and Applications, Springer, volume 125, issue 3, pages 543-558, June, DOI: 10.1007/s10957-005-2088-0.

Chapters

2022

  1. Marco Corazza & Giovanni Fasano, 2022, "Bitcoin Price Prediction: Mixed Integer Quadratic Programming Versus Machine Learning Approaches," Springer Books, Springer, in: Marco Corazza & Cira Perna & Claudio Pizzi & Marilena Sibillo, "Mathematical and Statistical Methods for Actuarial Sciences and Finance", DOI: 10.1007/978-3-030-99638-3_27.

2021

  1. Marco Corazza & Giovanni Fasano & Riccardo Gusso & Raffaele Pesenti, 2021, "Comparing RL Approaches for Applications to Financial Trading Systems," Springer Books, Springer, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo, "Mathematical and Statistical Methods for Actuarial Sciences and Finance", DOI: 10.1007/978-3-030-78965-7_22.

2012

  1. Marco Corazza & Giovanni Fasano & Riccardo Gusso, 2012, "Portfolio selection with an alternative measure of risk: Computational performances of particle swarm optimization and genetic algorithms," Springer Books, Springer, in: Cira Perna & Marilena Sibillo, "Mathematical and Statistical Methods for Actuarial Sciences and Finance", DOI: 10.1007/978-88-470-2342-0_15.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.