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 :
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Phone : 2610 997833
Fax : 2610 997313
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An advanced CNN-LSTM model for cryptocurrency forecasting |
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A dropout weight-constrained recurrent neural network model for forecasting the price of major cryptocurrencies and CCi30 index |
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High performance machine learning models of large-scale air-pollution data in urban area |
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A multiple input neural network model for predicting cotton production quantity |
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An alternating sum of Fibonacci and Lucas numbers of order k |
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A novel validation framework to enhance deep learning models in time-series forecasting |
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An advanced deep learning model for short-term forecasting U.S. natural gas price and movement |
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Investigating the problem of cryptocurrency price prediction - A deep learning approach |
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A CNN-LSTM model for gold price time series forecastings |
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On ensemble techniques of weight-constrained neural networks |
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An advanced active set L-BFGS algorithm for training constrained neural networks |
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Fuzzy Information Diffusion in Twitter by Considering User's Influence |
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Weight-constrained neural networks in forecasting tourist volumes: a case study |
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Forecasting stock price index movement using a constrained deep neural network training algorithm |
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An improved weight-constrained neural network training algorithm |
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An adaptive nonmonotone active set -weight constrained- neural network training algorithm |
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Forecasting economy-related data utilizing constrained recurrent neural networks |
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Employing constrained neural networks for forecasting new product's sales increase |
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An efficient preprocessing tool for supervised sentiment analysis on Twitter data |
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Predicting secondary structure for human proteins based on Chou-Fasman method |
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