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Ioannis E. Livieris

Ioannis E. Livieris received his B.Sc., M.Sc. and Ph.D. degrees in Mathematics from the University of Patras, Greece in 2006, 2008 and 2012 respectively. His research interests include numerical optimization, neural networks and its application in bioinformatics. He is a member of the ESDLab since 2008. See his personal web page.

 

 

Degrees

  • 2012: Ph.D. from Department of Mathematics, University of Patras.
  • 2008: M.Sc. in "Computational Mathematics & Informatics", Department of Mathematics, University of Patras, Greece.
  • 2006: Bachelor Degree in Mathematics (speciality in Computational Mathematics & Informatics), Department of Mathematics, University of Patras, Greece.

 

Dissertations

  • Ph.D. Thesis: Nonlinear Conjugate Gradient Methods for Optimization and Neural Network Training. Supervisor: Professor P. Pintelas.
  • M.Sc. Thesis: Performance Evaluation of Algorithms for Neural Network Training and Applications. Supevisor: Professor P. Pintelas.
  • B.Sc. Thesis: Constraint Propagation Problems. Bachelor Thesis Supevisor: Associate Professor T.N. Grapsa.

   

Courses

E-mail :      This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Phone :      2610 997833

Fax :          2610 997313




DSS-PSP - A decision support software for evaluating students' performance PDF Print E-mail

I.E. Livieris, K. Drakopoulou, Th. Kotsilieris, V. Tampakas and P. Pintelas. DSS-PSP - A decision support software for evaluating students’ performance. In 18th International Conference on Engineering Applications of Neural Networks (EANN 2017), 2017.

 
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A decision support system for predicting students’ performance PDF Print E-mail
 

I.E. Livieris, T.A. Mikropoulos and P. Pintelas. A decision support system for predicting students’ performance. Themes in Science & Technology Education, 9(1), 43-57, 2016

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A limited memory descent Perry conjugate gradient method PDF Print E-mail
 

I.E. Livieris and P. Pintelas. A limited memory descent Perry conjugate gradient method. Optimization Letters, 2016.

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A new class of nonmonotone conjugate gradient training algorithms PDF Print E-mail
I.E. Livieris and P. Pintelas, A new class of nonmonotone conjugate gradient training algorithms. Applied Mathematics and Computation, Volume 266, pp. 404-413, 2015.
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A modified Perry conjugate gradient method and its global convergence PDF Print E-mail
I.E. Livieris and P. Pintelas, A modified Perry conjugate gradient method and its global convergence. Optimization Letters, Volume 218, Number 18, p.p.

9197-9207, 2014.

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A new conjugate gradient algorithm for training neural networks based on a modified secant equation PDF Print E-mail
I.E. Livieris and P. Pintelas, A new conjugate gradient algorithm for training neural networks based on a modified secant equation. Applied Mathematics and Computation, Volume 221, p.p. 491-502, 2013.
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A new class of spectral conjugate gradient methods based on a modified secant equation for unconstrained optimization PDF Print E-mail
I.E. Livieris and P. Pintelas, A new class of spectral conjugate gradient methods based on a modified secant equation for unconstrained optimization. (accepted for publication), Journal of Computational and Applied Mathematics, 2012.
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Globally convergent modified Perry conjugate gradient method PDF Print E-mail
I.E. Livieris and P. Pintelas, Globally Convergent Modified Perry Conjugate Gradient Method, Applied Mathematics and Computation, 218(18), p.p. 9197-9207, 2012.
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An improved spectral conjugate gradient neural network training algorithm PDF Print E-mail

I.E. Livieris and P. Pintelas, An Improved Spectral Conjugate Gradient Neural Network Training Algorithm, International Journal on Artificial Intelligence and Tools, 20(1), 2012.

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A descent Dai-Liao conjugate gradient method based on a modified secant equation and its global convergence PDF Print E-mail

I.E. Livieris and P. Pintelas, A Descent Dai-Liao Conjugate Gradient Method Based on a Modified Secant Equation and Its Global Convergence, ISRN Computational Mathematics, 2012.

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An advanced conjugate gradient training algorithm based on a modified secant equation PDF Print E-mail

I.E. Livieris and P. Pintelas, An Advanced Conjugate Gradient Training Algorithm Based on a Modified Secant Equation, ISRN Artificial Intelligence, 2012.

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Predicting students' performance using artificial neural networks PDF Print E-mail
I.E. Livieris, K. Drakopoulou and P. Pintelas, Predicting students' performance using artificial neural networks, In the Proceddings of Information and Communication Technologies in Education, 2012.
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A memoryless BFGS Neural network training algorithm PDF Print E-mail

M.S. Apostolopoulou, D.G. Sotiropoulos, I.E. Livieris and P. Pintelas, A Memoryless BFGS Neural Network Training Algorithm, In Proceedings of 6th IEEE International Conference on Industrial Informatics (INDIN 2009), p.p. 216-221, 2009.

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Performance evaluation of descent CG methods for neural network training PDF Print E-mail

I.E. Livieris and P. Pintelas, Performance Evaluation of Descent CG Methods for Neural Network Training, In Proceedings of The 9th Hellenic European Research on Computer Mathematics & Conference its Applications (HERCMA 2009), vol 11, pp. 40-46, Athens, 2009.

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Classification of large biomedical data using ANNs based on BFGS method PDF Print E-mail

I.E. Livieris, M.S. Apostolopoulou, D.G. Sotiropoulos, S.A. Sioutas and P. Pintelas, Classification of Large Biomedical Data using ANNs based on BFGS method. In Proceedings of 13th Panhellenic Conference on Informatics (PCI 2009), 2009

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On descent spectral CG algorithms for training recurrent neural networks PDF Print E-mail

I.E. Livieris D.G. Sotiropoulos and P. Pintelas, On Descent Spectral CG Algorithms for Training Recurrent Neural Networks. In Proceedings of 13th Panhellenic Conference on Informatics (PCI 2009), 2009.

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A greedy approach to transversal selection for nonlinear systems of equations PDF Print E-mail

D.G. Sotiropoulos and I.E. Livieris A Greedy Approach to Transversal Selection for Nonlinear Systems of Equations, In Proceedings of Conference in Numerical Analysis (NumAn07), pp 134-136, Kalamata, September, 2007.

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