G. Magoulas

Vassilis P. Plagianakos, Michael N. Vrahatis, G. C. Meletiou, 2019, International Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004).

Intelligent multimedia transmission for back pain treatment

George Ghinea, Andrew O. Frank, George D. Magoulas, 2002 .

Improved processing of microarray data using image reconstruction techniques

G. Magoulas, Xiaohui Liu, P. O'Neill, 2003, IEEE Transactions on NanoBioscience.

Multivariable fuzzy controller design

R. E. King, G. D. Magoulas, A. A. Stathaki, 1994 .

Convolutional Neural Networks-Based Framework for Early Identification of Dementia Using MRI of Brain Asymmetry

Nitsa J. Herzog, G. Magoulas, 2022, Int. J. Neural Syst..

An Adaptive Fuzzy Model for Personalization with Evolvable User Profiles

G.D. Magoulas, D. Dimakopoulos, G. Magoulas, 2006, 2006 International Symposium on Evolving Fuzzy Systems.

Automated user modeling for personalized digital libraries

Enrique Frías-Martínez, Sherry Y. Chen, Robert D. Macredie, 2006, Int. J. Inf. Manag..

Improved Learning of Neural Nets Through Global Search

Vassilis P. Plagianakos, Michael N. Vrahatis, George D. Magoulas, 2006 .

Geometry of learning: visualizing the performance of neural network supervised training methods

Michael N. Vrahatis, George D. Magoulas, M. N. Vrahatis, 1997 .

Advanced Adaptive Nonmonotone Conjugate Gradient Training Algorithm for Recurrent Neural Networks

CHUN-CHENG PENG, GEORGE D. MAGOULAS, G. Magoulas, 2008, Int. J. Artif. Intell. Tools.

Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification

Daniel Stamate, George D. Magoulas, Ida Pu, 2021, EANN.

Improved sign-based learning algorithm derived by the composite nonlinear Jacobi process

Michael N. Vrahatis, George D. Magoulas, Aristoklis D. Anastasiadis, 2006 .

Effective neural network training with a different learning rate for each weight

V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, 1999, ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357).

Nonmonotone learning rules for backpropagation networks

V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, 1999, ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357).

On the alleviation of the problem of local minima in back-propagation

Michael N. Vrahatis, George D. Magoulas, M. N. Vrahatis, 1997 .

Improved Neural Network-based Interpretation of Colonoscopy Images Through On-line Learning and Evolution

Vassilis P. Plagianakos, Michael N. Vrahatis, George D. Magoulas, 2001 .

Improving the Particle Swarm Optimizer by Function “Stretching”

Vassilis P. Plagianakos, Michael N. Vrahatis, Konstantinos E. Parsopoulos, 2001 .

Dimensionality Reduction for Feature and Pattern Selection in Classification Problems

Z. Voulgaris, G.D. Magoulas, G. Magoulas, 2008, 2008 The Third International Multi-Conference on Computing in the Global Information Technology (iccgi 2008).

Development and convergence analysis of training algorithms with local learning rate adaptation

V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

A class of gradient unconstrained minimization algorithms with adaptive stepsize - some corrections

M. N. Vrahatis, G. Androulakis, G. Magoulas, 2000 .

Evolutionary approaches to signal decomposition in an application service management system

G. Magoulas, Tomasz D. Sikora, 2015, Soft Computing.

Under review as a conference paper at ICLR 2017

G. D. Magoulas, Alan Mosca, G. Magoulas, 2022 .

Distillation of Deep Learning Ensembles as a Regularisation Method

George D. Magoulas, Alan Mosca, Alan Mosca, 2018 .

Deep Learning of Brain Asymmetry Images and Transfer Learning for Early Diagnosis of Dementia

George D. Magoulas, Nitsa J. Herzog, G. Magoulas, 2021, EANN.