Ioannis E. Livieris
Ioannis E. Livieris
University of Patras, Department of Mathematics
Patvirtintas el. paštas - Pagrindinis puslapis
A CNN–LSTM model for gold price time-series forecasting
IE Livieris, E Pintelas, P Pintelas
Neural computing and applications 32, 17351-17360, 2020
An advanced CNN-LSTM model for cryptocurrency forecasting
IE Livieris, N Kiriakidou, S Stavroyiannis, P Pintelas
Electronics 10 (3), 287, 2021
Ensemble deep learning models for forecasting cryptocurrency time-series
IE Livieris, E Pintelas, S Stavroyiannis, P Pintelas
Algorithms 13 (5), 121, 2020
A grey-box ensemble model exploiting black-box accuracy and white-box intrinsic interpretability
E Pintelas, IE Livieris, P Pintelas
Algorithms 13 (1), 17, 2020
Predicting secondary school students' performance utilizing a semi-supervised learning approach
IE Livieris, K Drakopoulou, VT Tampakas, TA Mikropoulos, P Pintelas
Journal of educational computing research 57 (2), 448-470, 2019
Predicting students’ performance using artificial neural networks
IE Livieris, K Drakopoulou, P Pintelas
8th PanHellenic Conference with International Participation Information and …, 2012
Investigating the problem of cryptocurrency price prediction: a deep learning approach
E Pintelas, IE Livieris, S Stavroyiannis, T Kotsilieris, P Pintelas
Artificial Intelligence Applications and Innovations: 16th IFIP WG 12.5 …, 2020
A novel validation framework to enhance deep learning models in time-series forecasting
IE Livieris, S Stavroyiannis, E Pintelas, P Pintelas
Neural Computing & Applications 32, 17149–17167, 2020
A weighted voting ensemble self-labeled algorithm for the detection of lung abnormalities from X-rays
IE Livieris, A Kanavos, V Tampakas, P Pintelas
Algorithms 12 (3), 64, 2019
Gender recognition by voice using an improved self-labeled algorithm
IE Livieris, E Pintelas, P Pintelas
Machine Learning and Knowledge Extraction 1 (1), 492-503, 2019
A decision support system for predicting students’ performance
I Livieris, T Mikropoulos, P Pintelas
Themes in Science and Technology Education 9 (1), 43-57, 2016
Special issue on ensemble learning and applications
P Pintelas, IE Livieris
Algorithms 13 (6), 140, 2020
Explainable machine learning framework for image classification problems: case study on glioma cancer prediction
E Pintelas, M Liaskos, IE Livieris, S Kotsiantis, P Pintelas
Journal of imaging 6 (6), 37, 2020
A survey on algorithms for training artificial neural networks
I Livieris, P Pintelas
University of Patras, Department of Mathematics, Educational Software …, 2008
An ensemble SSL algorithm for efficient chest X-ray image classification
IE Livieris, A Kanavos, V Tampakas, P Pintelas
Journal of Imaging 4 (7), 95, 2018
On ensemble techniques of weight-constrained neural networks
IE Livieris, L Iliadis, P Pintelas
Evolving Systems 12, 155-167, 2021
Globally convergent modified Perry’s conjugate gradient method
IE Livieris, P Pintelas
Applied Mathematics and Computation 218 (18), 9197-9207, 2012
A new conjugate gradient algorithm for training neural networks based on a modified secant equation
IE Livieris, P Pintelas
Applied Mathematics and Computation 221, 491-502, 2013
A memoryless BFGS neural network training algorithm
MS Apostolopoulou, DG Sotiropoulos, IE Livieris, P Pintelas
2009 7th IEEE International Conference on Industrial Informatics, 216-221, 2009
A descent hybrid conjugate gradient method based on the memoryless BFGS update
IE Livieris, V Tampakas, P Pintelas
Numerical Algorithms 79, 1169-1185, 2018
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Straipsniai 1–20