Giovanni Fasano

Personal Details

First Name:	Giovanni
Middle Name:
Last Name:	Fasano
Suffix:
RePEc Short-ID:	pfa194
	https://mizar.unive.it/fasano/
	Department of Management Universita' Ca'Foscari Venezia San Giobbe, Cannaregio 873, 30121 Venezia, Italy
	+39-041-2346922

Affiliation

Dipartimento di Management
Università Ca' Foscari Venezia

Venezia, Italy
http://www.unive.it/management
RePEc:edi:mdvenit (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Marco Corazza & Giovanni Fasano & Riccardo Gusso & Raffaele Pesenti, 2019. "A comparison among Reinforcement Learning algorithms in financial trading systems," Working Papers 2019:33, Department of Economics, University of Venice "Ca' Foscari".

   Cited by:

   1. Yuling Huang & Kai Cui & Yunlin Song & Zongren Chen, 2023. "A Multi-Scaling Reinforcement Learning Trading System Based on Multi-Scaling Convolutional Neural Networks," Mathematics, MDPI, vol. 11(11), pages 1-19, May.

2. Mehiddin Al-Baali & Andrea Caliciotti & Giovanni Fasano & Massimo Roma, 2017. "Exploiting damped techniques for nonlinear conjugate gradient methods," DIAG Technical Reports 2017-05, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
   • 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), vol. 86(3), pages 501-522, December.

   Cited by:

   1. XiaoLiang Dong & Deren Han & Zhifeng Dai & Lixiang Li & Jianguang Zhu, 2018. "An Accelerated Three-Term Conjugate Gradient Method with Sufficient Descent Condition and Conjugacy Condition," Journal of Optimization Theory and Applications, Springer, vol. 179(3), pages 944-961, December.

3. Giovanni Fasano & Massimo Roma, 2015. "An estimation of the condition number for a class of indefinite preconditioned matrices," DIAG Technical Reports 2015-01, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".

   Cited by:

   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, vol. 65(2), pages 399-429, November.

4. Marco Corazza & Giacomo Di Tollo & Giovanni Fasano & Raffaele Pesenti, 2015. "A novel initialization of PSO for costly portfolio selection problems," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.

   Cited by:

   1. 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, vol. 44(1), pages 295-339, June.
   2. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2017. "PSO-based tuning of MURAME parameters for creditworthiness evaluation of Italian SMEs," Working Papers 04, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.

5. Giovanni Fasano, 2013. "A framework of conjugate direction methods for symmetric linear systems in optimization," Working Papers 31, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
   • Giovanni Fasano, 2015. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 883-914, March.
   • Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.

   Cited by:

   1. Giovanni Fasano & Raffaele Pesenti, 2017. "Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces," Journal of Optimization Theory and Applications, Springer, vol. 175(3), pages 764-794, December.

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

   Cited by:

   1. Marco Corazza & Giacomo Di Tollo & Giovanni Fasano & Raffaele Pesenti, 2015. "A novel initialization of PSO for costly portfolio selection problems," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.

7. Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part I," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
   • Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part II," Working Papers 5, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.

   Cited by:

   1. Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part II," Working Papers 5, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
      • Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part I," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.

8. Marco Corazza & Giovanni Fasano & Riccardo Gusso, 2011. "Particle Swarm Optimization with non-smooth penalty reformulation for a complex portfolio selection problem," Working Papers 2011_10, Department of Economics, University of Venice "Ca' Foscari".

   Cited by:

   1. Honghao Zhang & Yong Peng & Guangdong Tian & Danqi Wang & Pengpeng Xie, 2017. "Green material selection for sustainability: A hybrid MCDM approach," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-26, May.
   2. Ren‐Raw Chen & Wiliam Kaihua Huang & Shih‐Kuo Yeh, 2021. "Particle swarm optimization approach to portfolio construction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(3), pages 182-194, July.
   3. K. Liagkouras & K. Metaxiotis, 2018. "A new efficiently encoded multiobjective algorithm for the solution of the cardinality constrained portfolio optimization problem," Annals of Operations Research, Springer, vol. 267(1), pages 281-319, August.
   4. Alejandro Estrada-Moreno & Albert Ferrer & Angel A. Juan & Javier Panadero & Adil Bagirov, 2020. "The Non-Smooth and Bi-Objective Team Orienteering Problem with Soft Constraints," Mathematics, MDPI, vol. 8(9), pages 1-16, September.
   5. 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, vol. 44(1), pages 295-339, June.
   6. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2017. "PSO-based tuning of MURAME parameters for creditworthiness evaluation of Italian SMEs," Working Papers 04, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
   7. Marco Corazza & Giacomo Di Tollo & Giovanni Fasano & Raffaele Pesenti, 2015. "A novel initialization of PSO for costly portfolio selection problems," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
   8. 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, vol. 304(1), pages 109-137, September.
   9. Keshvari, Abolfazl, 2017. "A penalized method for multivariate concave least squares with application to productivity analysis," European Journal of Operational Research, Elsevier, vol. 257(3), pages 1016-1029.

9. Andrea Ellero & Giovanni Fasano & Annamaria Sorato, 2008. "A Modified Galam's Model," Working Papers 180, Department of Applied Mathematics, Università Ca' Foscari Venezia.

   Cited by:

   1. Han, Shuo & Zhuang, Fuzhen & He, Qing & Shi, Zhongzhi & Ao, Xiang, 2014. "Energy model for rumor propagation on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 99-109.
   2. Tian, Ru-Ya & Zhang, Xue-Fu & Liu, Yi-Jun, 2015. "SSIC model: A multi-layer model for intervention of online rumors spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 181-191.

Articles

1. 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, vol. 186(2), pages 554-589, August.

   Cited by:

   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, vol. 65(2), pages 399-429, November.
   2. Giovanni Fasano & Raffaele Pesenti, 2017. "Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces," Journal of Optimization Theory and Applications, Springer, vol. 175(3), pages 764-794, December.
   3. Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part II," Working Papers 5, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
      • Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part I," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
   4. Marco Corazza & Giacomo Di Tollo & Giovanni Fasano & Raffaele Pesenti, 2015. "A novel initialization of PSO for costly portfolio selection problems," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
   5. Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.
      • Giovanni Fasano, 2013. "A framework of conjugate direction methods for symmetric linear systems in optimization," Working Papers 31, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
      • Giovanni Fasano, 2015. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 883-914, March.
   6. Giovanni Fasano & Massimo Roma, 2013. "Preconditioning Newton–Krylov methods in nonconvex large scale optimization," Computational Optimization and Applications, Springer, vol. 56(2), pages 253-290, October.
   7. 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, vol. 77(3), pages 627-651, December.

2. Caliciotti, Andrea & Fasano, Giovanni & Roma, Massimo, 2018. "Preconditioned Nonlinear Conjugate Gradient methods based on a modified secant equation," Applied Mathematics and Computation, Elsevier, vol. 318(C), pages 196-214.

   Cited by:

   1. Mehiddin Al-Baali & Andrea Caliciotti & Giovanni Fasano & Massimo Roma, 2017. "Exploiting damped techniques for nonlinear conjugate gradient methods," DIAG Technical Reports 2017-05, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
      • 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), vol. 86(3), pages 501-522, December.
   2. Abdul Wahid & Javed Iqbal & Affaq Qamar & Salman Ahmed & Abdul Basit & Haider Ali & Omar M. Aldossary, 2020. "A Novel Power Scheduling Mechanism for Islanded DC Microgrid Cluster," Sustainability, MDPI, vol. 12(17), pages 1-14, August.

3. 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, vol. 71(1), pages 73-93, September.

   Cited by:

   1. Falcone, Alberto & Garro, Alfredo & Mukhametzhanov, Marat S. & Sergeyev, Yaroslav D., 2021. "A Simulink-based software solution using the Infinity Computer methodology for higher order differentiation," Applied Mathematics and Computation, Elsevier, vol. 409(C).
   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, vol. 186(2), pages 554-589, August.
   3. 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, vol. 77(3), pages 627-651, December.

4. Giovanni Fasano & Raffaele Pesenti, 2017. "Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces," Journal of Optimization Theory and Applications, Springer, vol. 175(3), pages 764-794, December.

   Cited by:

   1. 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, vol. 186(2), pages 554-589, August.
   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, vol. 71(1), pages 73-93, September.

5. 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), vol. 86(3), pages 501-522, December.
   • Mehiddin Al-Baali & Andrea Caliciotti & Giovanni Fasano & Massimo Roma, 2017. "Exploiting damped techniques for nonlinear conjugate gradient methods," DIAG Technical Reports 2017-05, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
   See citations under working paper version above.
6. 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, vol. 65(2), pages 399-429, November.

   Cited by:

   1. Andrzej Stachurski, 2017. "On a conjugate directions method for solving strictly convex QP problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 86(3), pages 523-548, December.
   2. Caliciotti, Andrea & Fasano, Giovanni & Roma, Massimo, 2018. "Preconditioned Nonlinear Conjugate Gradient methods based on a modified secant equation," Applied Mathematics and Computation, Elsevier, vol. 318(C), pages 196-214.
   3. Mehiddin Al-Baali & Andrea Caliciotti & Giovanni Fasano & Massimo Roma, 2017. "Exploiting damped techniques for nonlinear conjugate gradient methods," DIAG Technical Reports 2017-05, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
      • 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), vol. 86(3), pages 501-522, December.

7. Giovanni Fasano, 2015. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 883-914, March.
   • Giovanni Fasano, 2013. "A framework of conjugate direction methods for symmetric linear systems in optimization," Working Papers 31, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
   • Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.
   See citations under working paper version above.
8. Giovanni Fasano & Massimo Roma, 2013. "Preconditioning Newton–Krylov methods in nonconvex large scale optimization," Computational Optimization and Applications, Springer, vol. 56(2), pages 253-290, October.

   Cited by:

   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, vol. 65(2), pages 399-429, November.
   2. Giovanni Fasano & Raffaele Pesenti, 2017. "Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces," Journal of Optimization Theory and Applications, Springer, vol. 175(3), pages 764-794, December.
   3. Caliciotti, Andrea & Fasano, Giovanni & Roma, Massimo, 2018. "Preconditioned Nonlinear Conjugate Gradient methods based on a modified secant equation," Applied Mathematics and Computation, Elsevier, vol. 318(C), pages 196-214.
   4. C. P. Brás & J. M. Martínez & M. Raydan, 2020. "Large-scale unconstrained optimization using separable cubic modeling and matrix-free subspace minimization," Computational Optimization and Applications, Springer, vol. 75(1), pages 169-205, January.
   5. Mehiddin Al-Baali & Andrea Caliciotti & Giovanni Fasano & Massimo Roma, 2017. "Exploiting damped techniques for nonlinear conjugate gradient methods," DIAG Technical Reports 2017-05, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
      • 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), vol. 86(3), pages 501-522, December.
   6. Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.
      • Giovanni Fasano, 2013. "A framework of conjugate direction methods for symmetric linear systems in optimization," Working Papers 31, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
      • Giovanni Fasano, 2015. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 883-914, March.
   7. 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, vol. 77(3), pages 627-651, December.

9. 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, vol. 6(6), pages 765-784.

   Cited by:

   1. Marco Corazza & Giacomo Di Tollo & Giovanni Fasano & Raffaele Pesenti, 2015. "A novel initialization of PSO for costly portfolio selection problems," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.

10. 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, vol. 388(18), pages 3901-3910.

    Cited by:

    1. Sarkar, Shubhayan & Benjamin, Colin, 2019. "Entanglement renders free riding redundant in the thermodynamic limit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 607-613.
    2. Han, Shuo & Zhuang, Fuzhen & He, Qing & Shi, Zhongzhi & Ao, Xiang, 2014. "Energy model for rumor propagation on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 99-109.
    3. Tian, Ru-Ya & Zhang, Xue-Fu & Liu, Yi-Jun, 2015. "SSIC model: A multi-layer model for intervention of online rumors spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 181-191.
    4. Andrea Ellero & Annamaria Sorato & Giovanni Fasano, 2011. "A new model for estimating the probability of information spreading with opinion leaders," Working Papers 13, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    5. Alatas, Husin & Nurhimawan, Salamet & Asmat, Fikri & Hardhienata, Hendradi, 2017. "Dynamics of an agent-based opinion model with complete social connectivity network," Chaos, Solitons & Fractals, Elsevier, vol. 101(C), pages 24-32.

11. G. Fasano, 2007. "Lanczos Conjugate-Gradient Method and Pseudoinverse Computation on Indefinite and Singular Systems," Journal of Optimization Theory and Applications, Springer, vol. 132(2), pages 267-285, February.

    Cited by:

    1. Giovanni Fasano, 2008. "Notes on a 3-term Conjugacy Recurrence for the Iterative Solution of Symmetric Linear Systems," Working Papers 179, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    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, vol. 186(2), pages 554-589, August.
    3. Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.
       • Giovanni Fasano, 2013. "A framework of conjugate direction methods for symmetric linear systems in optimization," Working Papers 31, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
       • Giovanni Fasano, 2015. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 883-914, March.
    4. 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, vol. 71(1), pages 73-93, September.
    5. Giovanni Fasano & Massimo Roma, 2013. "Preconditioning Newton–Krylov methods in nonconvex large scale optimization," Computational Optimization and Applications, Springer, vol. 56(2), pages 253-290, October.
    6. 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, vol. 77(3), pages 627-651, December.

12. G. Fasano, 2005. "Planar Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization, Part 2: Application," Journal of Optimization Theory and Applications, Springer, vol. 125(3), pages 543-558, June.

    Cited by:

    1. G. Fasano, 2007. "Lanczos Conjugate-Gradient Method and Pseudoinverse Computation on Indefinite and Singular Systems," Journal of Optimization Theory and Applications, Springer, vol. 132(2), pages 267-285, February.
    2. Giovanni Fasano & Raffaele Pesenti, 2017. "Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces," Journal of Optimization Theory and Applications, Springer, vol. 175(3), pages 764-794, December.
    3. 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, vol. 186(2), pages 554-589, August.
    4. Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.
       • Giovanni Fasano, 2013. "A framework of conjugate direction methods for symmetric linear systems in optimization," Working Papers 31, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
       • Giovanni Fasano, 2015. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 883-914, March.
    5. 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, vol. 71(1), pages 73-93, September.
    6. Giovanni Fasano & Massimo Roma, 2013. "Preconditioning Newton–Krylov methods in nonconvex large scale optimization," Computational Optimization and Applications, Springer, vol. 56(2), pages 253-290, October.
    7. 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, vol. 77(3), pages 627-651, December.

13. G. Fasano, 2005. "Planar Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization, Part 1: Theory," Journal of Optimization Theory and Applications, Springer, vol. 125(3), pages 523-541, June.

    Cited by:

    1. G. Fasano, 2007. "Lanczos Conjugate-Gradient Method and Pseudoinverse Computation on Indefinite and Singular Systems," Journal of Optimization Theory and Applications, Springer, vol. 132(2), pages 267-285, February.
    2. 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, vol. 65(2), pages 399-429, November.
    3. Giovanni Fasano & Raffaele Pesenti, 2017. "Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces," Journal of Optimization Theory and Applications, Springer, vol. 175(3), pages 764-794, December.
    4. Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part II," Working Papers 5, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
       • Giovanni Fasano & Massimo Roma, 2011. "A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part I," Working Papers 4, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    5. 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, vol. 186(2), pages 554-589, August.
    6. Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.
       • Giovanni Fasano, 2013. "A framework of conjugate direction methods for symmetric linear systems in optimization," Working Papers 31, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
       • Giovanni Fasano, 2015. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 883-914, March.
    7. 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, vol. 71(1), pages 73-93, September.
    8. Giovanni Fasano & Massimo Roma, 2013. "Preconditioning Newton–Krylov methods in nonconvex large scale optimization," Computational Optimization and Applications, Springer, vol. 56(2), pages 253-290, October.
    9. Shi, Zhen-Jun & Shen, Jie, 2007. "Convergence of Liu-Storey conjugate gradient method," European Journal of Operational Research, Elsevier, vol. 182(2), pages 552-560, October.
    10. 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, vol. 77(3), pages 627-651, December.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 10 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-CMP: Computational Economics (8) 2008-12-01 2011-08-15 2011-11-01 2013-07-05 2015-08-30 2017-03-26 2017-06-04 2020-02-03. Author is listed
2. NEP-ORE: Operations Research (5) 2013-12-29 2015-08-30 2017-03-26 2019-12-16 2020-02-03. Author is listed
3. NEP-DCM: Discrete Choice Models (1) 2017-06-04
4. NEP-GER: German Papers (1) 2015-08-30
5. NEP-MAC: Macroeconomics (1) 2020-02-03

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To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

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