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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




A decision support software for forecasting patient’s length of stay PDF Print E-mail

I.E. Livieris, T. Kotsilieris, I. Dimopoulos and P. Pintelas. A decision support software for forecasting patient’s length of stay. Algorithms, 2018.

 
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An identity relating Fibonacci and Lucas numbers of order k PDF Print E-mail

S.D. Dafnis, A.N. Philippou and I.E. Livieris, An identity relating Fibonacci and Lucas numbers of order k. Electronic Notes in Discrete Mathematics, Volume 70, pp. 37-42,
2018.

 
 
A new ensemble self-labeled semi-supervised algorithm PDF Print E-mail

I.E. Livieris. A new ensemble self-labeled semi-supervised algorithm. Informatica, Volume 43, pp. 221-234, 2019.

 
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Improving the classification efficiency of an ANN utilizing a new training methodology PDF Print E-mail
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Predicting anxiety disorders and suicide tendency using machine learning: a review PDF Print E-mail

T. Kotsilieris, E. Pintelas, I.E. Livieris and P. Pintelas. Predicting anxiety disorders and suicide tendency using machine learning: a review. International Journal of Medical Engineering and Informatics, 2019

 
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