Vassilis Plagianakos

Professor · Computer Science & Biomedical Informatics · University of Thessaly

Publications

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Journals

2026

  1. P.N. Sakellariou, S.V. Georgakopoulos, S. Tasoulis, V.P. Plagianakos, Binary black hole parameter estimation with hybrid CNN-transformer neural networks, Astronomy and Computing, Vol. 54, 101027, 2026.
  2. P. Anangnostou, S.K. Tasoulis, A.G. Vrahatis, S.V. Georgakopoulos, V.P. Plagianakos, Boosting neural network performance for high dimensional data through random projections, Pattern Recognition Letters, Vol. 199, 149–155, 2026.

2025

  1. P. Barmpas, P. Anagnostou, S. Tasoulis, V.P. Plagianakos, S. Georgakopoulos, Efficient hybrid hierarchical clustering with incremental silhouette score for large noisy datasets, International Journal of Neural Systems, 2550076, 2025.
  2. P.V. Tsakmaki, S. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Reducing artifact preprocessing in heart rate variability-based personalized psychosis prediction using adaptive long short-term memory models, International Journal of Neural Systems, 2025.
  3. P.C. Theocharopoulos, P. Anagnostou, S.V. Georgakopoulos, S.K. Tasoulis, V.P. Plagianakos, Large language models for efficient topic modeling, Neural Computing and Applications, 2025.

2024

  1. G. Skoufos, P. Kakoulidis, S. Tastsoglou, E. Zacharopoulou, V. Kotsira, M. Miliotis, G. Mavromati, D. Grigoriadis, M. Zioga, A. Velli, I. Koutou, D. Karagkouni, S. Stavropoulos, F.S. Kardaras, A. Lifousi, E. Vavalou, A. Ovsepian, A. Skoulakis, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, A.G. Hatzigeorgiou, TarBase-v9.0 extends experimentally supported miRNA-gene interactions to cell-types and virally encoded miRNAs, Nucleic Acids Research, Vol. 52, 304-310, 2024.
  2. K-M. Stathopoulou, S.V. Georgakopoulos, S. Tasoulis, V.P. Plagianakos, Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation, Health Information Science and Systems, Vol. 12 (1), 2024.
  3. P.C. Theocharopoulos, S. Bersimis, S.V. Georgakopoulos, A. Karaminas, S.K. Tasoulis, V.P. Plagianakos, Developing predictive precision medicine models by exploiting real-world data using machine learning methods, Journal of Applied Statistics, 1–24, 2024.

2023

  1. I.A. Nellas, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Two phase cooperative learning for supervised dimensionality reduction, Pattern Recognition, 109871, 2023.
  2. P.C. Theocharopoulos, A. Tsoukala, S.V. Georgakopoulos, S.K. Tasoulis, V.P. Plagianakos, Analysing sentiment change detection of COVID-19 tweets, Neural Computing and Applications, 2023.
  3. P. Anagnostou, S.K. Tasoulis, V.P. Plagianakos, D.K. Tasoulis, Hipart: Hierarchical divisive clustering toolbox, Journal of Open Source Software, Vol. 8 (84), 5024, 2023.

2022

  1. P. Barmpas, S. Tasoulis, A.G. Vrahatis, S.V. Georgakopoulos, P. Anagnostou, M. Prina, J.L. Ayuso-Mateos, J. Bickenbach, I. Bayes, M. Bobak, F.F. Caballero, S. Chatterji, L. Egea-Cortés, E. García-Esquinas, M. Leonardi, S. Koskinen, I. Koupil, A. Pajak, M. Prince, W. Sanderson, S. Scherbov, A. Tamosiunas, A. Galas, J.M. Haro, A. Sanchez-Niubo, V.P. Plagianakos, D. Panagiotakos, A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the Αthlos project, Health Information Science and Systems, Vol. 10 (1), 2022.
  2. L. Negka, A. Katsika, G. Spathoulas, V.P. Plagianakos, Blockchain state channels with compact states through the use of RSA accumulators, Blockchain: Research and Applications, 2022.

2021

  1. P. Anagnostou, S. Tasoulis, A. G. Vrahatis, S. Georgakopoulos, M. Prina, J. L. Ayuso-Mateos, J. Bickenbach, I. Bayes-Marin, F. F. Caballero, L. Egea-Cortés, E. García-Esquinas, M. Leonardi, S. Scherbov, A. Tamosiunas, A. Galas, J. M. Haro, A. Sanchez-Niubo, V. Plagianakos, D. Panagiotakos, Enhancing the human health status prediction: The athlos project, Applied Artificial Intelligence, Vol. 1–23, 2021.
  2. I. Lampropoulos, D. Raptis, Z. Daniil, S. Tasoulis, V. Plagianakos, F. Malli, K. Gourgoulianis, Temporal trends in pulmonary embolism prevalence in Greece during 2013–2017, BMC Public Health, Vol. 21, 559, 2021.

2020

  1. A. Vassiliou, C. Georgakopoulou, A. Papageorgiou, S.V. Georgakopoulos, S. Goulas, T. Paschalis, P. Paterakis, P. Gallos, D. Kyriazis, V.P. Plagianakos, Health in all Policy Making Utilizing Big Data, Acta Informatica Medica, Vol. 28, 65-70, 2020.
  2. K. Moutselos, I. Maglogiannis, D. Kyriazis, A. Gil Granados, V.P. Plagianakos, A. Papageorgiu, S. Nechifor, J. Mantas, A. Magdalinou, L. Montandon, Modelling and Evaluation of Policies, Acta Informatica Medica, Vol. 28 (1), 58, 2020.
  3. A.G. Vrahatis, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Ensemble Classification through Random Projections for Single-Cell RNA-seq Data, Information, Vol. 11 (11), 502, 2020.
  4. S.V. Georgakopoulos, S.K. Tasoulis, G.I. Mallis, A.G. Vrahatis, V.P. Plagianakos, I. Maglogiannis, Change Detection and Convolution Neural Networks for Fall Recognition, Neural Computing and Applications, Vol. 32 (23), 17245-17258, 2020.

2019

  1. D. Kyriazis, S. Autexier, M. Boniface, V. Engen, R. Jimenez-Peris, B. Jordan, G. Jurak, A. Kiourtis, T. Kosmidis, M. Lustrek, I. Maglogiannis, J. Mantas, A. Martinez, A. Mavrogiorgou, A. Menychtas, L. Montandon, C.S. Nechifor, S. Nifakos, A. Papageorgiou, M. Patino-Martinez, M. Perez, V.P. Plagianakos, D. Stanimirovic, G. Starc, T. Tomson, F. Torelli, V. Traver-Salcedo, G. Vassilacopoulos, A. Magdalinou, U. Wajid, The CrowdHEALTH project and the Hollistic Health Records: Collective Wisdom Driving Public Health Policies, Acta Informatica Medica, Vol. 27, 369-373, 2019.
  2. S.V. Georgakopoulos, K. Kottari, K. Delibasis, V.P. Plagianakos, I. Maglogiannis, Improving the performance of convolutional neural network for skin image classification using the response of image analysis filters, Neural Computing and Applications, Vol. 6, 1805-1822, 2019.

2018

  1. S.V. Georgakopoulos, K. Kottari, K. Delibasis, V.P. Plagianakos, I. Maglogiannis, Pose Recognition Using Convolutional Neural Networks on Omni-directional Images, Neurocomputing, Vol. 280, 23-31, 2018.
  2. Manolis Koubarakis, George Vouros, Georgios Chalkiadakis, Vassilis Plagianakos, Christos Tjortjis, Ergina Kavallieratou, Dimitris Vrakas, Nikolaos Mavridis, Georgios Petasis, Konstantinos Blekas, Anastasia Krithara, AI in Greece: The Case of Research on Linked Geospatial Data, AI Magazine, Vol. 39, 91-96, 2018.
  3. D.K. Iakovidis, S.V. Georgakopoulos, M. Vasilakakis, A. Koulaouzidis, V.P. Plagianakos, Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification, IEEE Transactions on Medical Imaging, Vol. 37, 2196-2210, 2018.

2017

  1. K. Kottari, K.K. Delibasis, V.P. Plagianakos, Real Time Vision-based Measurements for Quality Control of Industrial Rods on a Moving Conveyor, Multimedia Tools and Applications, 1-18, 2017.

2016

  1. K.K. Delibasis, S.V. Georgakopoulos, K. Kottari, V.P. Plagianakos, I. Maglogiannis, Geodesically-corrected Zernike descriptors for pose recognition in omni-directional images, Integrated Computer-Aided Engineering, Vol. 23, 185-199, 2016.

2015

  1. I. Maglogiannis, S.V. Georgakopoulos, S.K. Tasoulis, V.P. Plagianakos, A Software Tool for the Automatic Detection and Quantification of Fibrotic Tissues in Microscopy Images, Information Sciences, Vol. 308, 125-139, 2015.
  2. K.K. Delibasis, V.P. Plagianakos, I. Maglogiannis, Estimation of Robot Position and Orientation Using a Stationary Fisheye Camera, International Journal on Artificial Intelligence Tools, Vol. 24, 1560004, 2015.

2014

  1. V.P. Plagianakos, Unsupervised Clustering and Multi-Optima Evolutionary Search, Engineering Intelligent Systems, Vol. 22, 2014.
  2. K.K. Delibasis, I. Maglogiannis, V.P. Plagianakos, Refinement of Human Silhouette Segmentation in Omni-Directional Indoor Videos analysis, Computer Vision and Image Understanding, Vol. 128, 65-83, 2014.

2013

  1. S.K. Tasoulis, D.K. Tasoulis, V.P. Plagianakos, Random Direction Divisive Clustering, Pattern Recognition Letters, Vol. 34, 131-139, 2013.
  2. S.K. Tasoulis, C.N. Doukas, V.P. Plagianakos, I. Maglogiannis, Statistical Data Mining of Streaming Motion Data for Activity and Fall Recognition in Assistive Environments, Neurocomputing, Vol. 107, 87-96, 2013.
  3. S.K. Tasoulis, V.P. Plagianakos, I. Maglogiannis, Fractal analysis and fuzzy c-means clustering for quantification of fibrotic microscopy images, Artificial Intelligence Review, 1-17, 2013.

2012

  1. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution: A hybrid approach, Information Sciences, Vol. 216, 50-92, 2012.

2011

  1. M.G. Epitropakis, D.K. Tasoulis, N.G. Pavlidis, V.P. Plagianakos, M.N. Vrahatis, Enhancing Differential Evolution Utilizing Proximity-based Mutation Operators, IEEE Transactions on Evolutionary Computation, Vol. 15, 99-119, 2011.

2010

  1. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Hardware-Friendly Higher-Order Neural Network Training Using Distributed Evolutionary Algorithms, Applied Soft Computing, Vol. 10, 398-408, 2010.
  2. S.K. Tasoulis, D.K. Tasoulis, V.P. Plagianakos, Enhancing Principal Direction Divisive Clustering, Pattern Recognition, Vol. 43, 3391-3411, 2010.

2006

  1. N.G. Pavlidis, V.P. Plagianakos, D.K. Tasoulis, M.N. Vrahatis, Financial Forecasting Through Unsupervised Clustering and Neural Networks, Operations Research, Vol. 6, 103-127, 2006.
  2. N.G. Pavlidis, D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Computational Intelligence Methods for Financial Time Series Modeling, International Journal of Bifurcation and Chaos, Vol. 16, 2053-2062, 2006.
  3. D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Unsupervised clustering in mRNA expression profiles, Computers in Biology and Medicine, Vol. 36, 1126-1142, 2006.
  4. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Distributed Computing Methodology for Training Neural Networks in an Image-guided Diagnostic Application, Computer Methods and Programs in Biomedicine, Vol. 81, 228–235, 2006.
  5. D.K. Tasoulis, P. Spyridonos, N.G. Pavlidis, V.P. Plagianakos, P. Ravazoula, G. Nikiforidis, M.N. Vrahatis, Cell-nuclear data reduction and prognostic model selection in bladder tumor recurrence, Artificial Intelligence In Medicine, Vol. 38, 291-303, 2006.

2005

  1. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Evolutionary Training of Hardware Realizable Multilayer Perceptrons, Neural Computing and Application, Vol. 15, 33-40, 2005.

2004

  1. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Neural network-based colonoscopic diagnosis using on-line learning and differential evolution, Applied Soft Computing, Vol. 4, 369-379, 2004.

2003

  1. M.N. Vrahatis, G.D. Magoulas, V.P. Plagianakos, From linear to nonlinear iterative methods, Applied Numerical Mathematics, Vol. 45, 59-77, 2003.

2002

  1. N.A. Katsanos, F. Roubani-Kalantzopoulou, E. Iliopoulou, I. Bassiotis, V. Siokos, M.N. Vrahatis, V.P. Plagianakos, Lateral Molecular Interactions on Heterogeneous Surfaces Experimentally Measured, Colloid Surfaces A, Vol. 201, 173-180, 2002.
  2. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Globally Convergent Algorithms with Local Learning Rates, IEEE Transactions on Neural Networks, Vol. 13, 774-779, 2002.
  3. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Deterministic Nonmonotone Strategies for Effective Training of Multi-Layer Perceptrons, IEEE Transactions on Neural Networks, Vol. 13, 1268-1284, 2002.
  4. V.P. Plagianakos, M.N. Vrahatis, Parallel Evolutionary Training Algorithms for `Hardware-Friendly' Neural Networks, Natural Computing, Vol. 1, 307-322, 2002.

2001

  1. V.P. Plagianakos, N.K. Nousis, M.N. Vrahatis, Locating and Computing in Parallel all the Simple Roots of Special Functions Using PVM, Journal of Computational and Applied Mathematics, Vol. 133, 545-554, 2001.
  2. G.D. Magoulas, V.P. Plagianakos, G.S. Androulakis, M.N. Vrahatis, A Framework for the Development of Globally Convergent Adaptive Learning Rate Algorithms, International Journal of Computer Research, Vol. 10 (1), 1-10, 2001.
  3. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Adaptive stepsize algorithms for on-line training of neural networks, Nonlinear Analysis, Theory, Methods and Applications, Vol. 47, 3425-3430, 2001.
  4. K.E. Parsopoulos, V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Objective function “stretching” to alleviate convergence to local minima, Nonlinear Analysis, Theory, Methods and Applications, Vol. 47, 3419-3424, 2001.
  5. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Learning in multilayer perceptrons using global optimization strategies, Nonlinear Analysis, Theory, Methods and Applications, Vol. 47, 3431-3436, 2001.
  6. N.A. Katsanos, E. Iliopoulou, V.P. Plagianakos, H. Mangou, Interrelations between Absorption Energiesand Local Isotherms, Local Monolayer Capabilities, and Energy Distribution Functions, as Determined for Heterogeneous Surfaces by Inverse Gas Chromatography, Journal of Colloid and Interface Science, Vol. 239, 10-19, 2001.
  7. F. Roubani-Kalantzopoulou, T. Artemiadi, I. Bassiotis, N.A. Katsanos, V.P. Plagianakos, Time separation of Absorption Sites on Heterogeneous Surfaces by Inverse Gas Chromatography, Chromatographia, Vol. 53, 315-320, 2001.

2000

  1. M.N. Vrahatis, G.D. Magoulas, V.P. Plagianakos, Globally Convergent Modification of the Quickprop Method, Neural Processing Letters, Vol. 12 (2), 159-170, 2000.

Edited Volumes

2019

  1. Y. Manolopoulos, V.P. Plagianakos (eds.), Special Issue on Selected Papers from AIAI/EAIS 2018 Conferences on Applications of Data Mining Operations, International Journal on Artificial Intelligence Tools, Vol. 28 (08), 2019.

2012

  1. Ilias Maglogiannis, Vassilis Plagianakos, Ioannis Vlahavas (eds.), Artificial Intelligence: Theories and Applications, Proceedings of the 7th Hellenic Conference on AI, Lecture Notes in Computer Science, LNCS/LNAI, Vol. 7297, 2012.

Conference Proceedings

2025

  1. P.V. Tsakmaki, S. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, LSTM-based Classification of Psychiatric Disorders using Ultra-short Raw ECG Signals, In: 2025 IEEE Symposium on Computational Intelligence in Health and Medicine (IEEE CIHM 2025), 1–7, 2025.
  2. P.C. Theocharopoulos, S. Bersimis, S.V. Georgakopoulos, V.P. Plagianakos, S.K. Tasoulis, Transforming Medical Practice: Harnessing the Power of Big Data and Machine Learning for Predictive Precision Medicine, In: 2025 IEEE Symposium on Computational Intelligence in Health and Medicine (IEEE CIHM 2025), 1–7, 2025.
  3. A. Bilioni, P. Anagnostou, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Enhancing machine learning models for medical coding: Diagnostic codes mapping and synthetic clinical notes, In: 2025 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 1-8, 2025.
  4. K. Tsiaktani, P. Anagnostou, S.K. Tasoulis, S.V. Georgakopoulos, J.A. Gittings, D.E. Raitsos, A. Sergounioti, V.P. Plagianakos, Short-term impacts of weather conditions on biomarkers among urban adults in Greece, In: 2025 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 1-8, 2025.

2024

  1. S. Stavropoulos, E. Zacharopoulou, S.V. Georgakopoulos, S. Tasoulis, V.P. Plagianakos, A.G. Hatzigeorgiou, Leveraging Large Language Models for Information Extraction: Identifying microRNA-gene Interactions in Biomedical Literature, In: 2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2024), 1–7, 2024.
  2. P.V. Tsakmaki, S. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Harnessing LSTMs for Enhanced Prediction of Psychotic Episodes in Schizophrenia Spectrum, In: 2024 IEEE Congress on Evolutionary Computation (IEEE CEC 2024), 1–8, 2024.
  3. P. Barmpas, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Hyperdimensional Computing Approaches in Single Cell RNA Sequencing Classification, In: 2024 IEEE Congress on Evolutionary Computation (IEEE CEC 2024), 1–8, 2024.

2023

  1. P. Anagnostou, P. Barmpas, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Neural Networks Voting for Projection Based Ensemble Classifiers, In: 2023 IEEE International Conference on Big Data (IEEE BigData 2023), 4567–4574, 2023.
  2. P.C. Theocharopoulos, P. Anagnostou, A. Tsoukala, S.V. Georgakopoulos, S.K. Tasoulis, V.P. Plagianakos, Detection of Fake Generated Scientific Abstracts, In: 2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (IEEE BigDataService 2023), 33–39, 2023.

2022

  1. K-P.Lazaros, S. Tasoulis, A. Vrahatis, V.P. Plagianakos, Feature Selection for High Dimensional Data using Supervised Machine Learning Techniques, In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022), 3891–3894, 2022.
  2. S.V. Georgakopoulos, S.K. Tasoulis, A.G. Vrahatis, S. Moustakidis, D.E. Tsaopoulos, V.P. Plagianakos, Deep Hybrid Learning for Anomaly Detection in Behavioral Monitoring, In: 2022 IEEE International Joint Conference on Neural Networks (IEEE IJCNN 2022), 1–9, 2022.

2021

  1. I. Nellas, S. Tasoulis, V. Plagianakos, Convolutional Variational Autoencoders for Image Clustering, In: Proceedings of the 2021 International Conference on Data Mining Workshops (ICDMW), 695-702, 2021.

2020

  1. G. Kostikidis, P. Gallos, I.S. Triantafyllou, V.P. Plagianakos, Citizens' Opinions about a Digital Health Insurance Record, In: Proceedings of the 2020 Special Topic Conference of the European Federation for Medical Informatics (EFMI STC 2020), Studies in Health Technology and Informatics, Integrated Citizen Centered Digital Health and Social Care, Vol. 262, 230–232, 2020.
  2. K. Delibasis, S.V. Georgakopoulos, S.K. Tasoulis, I. Maglogiannis, V.P. Plagianakos, On Image Prefiltering for Skin Lesion Characterization Utilizing Deep Transfer Learning, In: Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN2020), 377-388, 2020.
  3. S.V. Georgakopoulos, P. Gallos, V.P. Plagianakos, How to Extract and Explore Big Data for Fraud Detection in the Healthcare Sector: The EOPYY Case Study, In: Proceedings of the Medical Informatics Europe (MIE2020), Studies in Health Technology and Informatics, Digital Personalized Health and Medicine, IOS Press, Vol. 270, 1307–1308, 2020.
  4. S.V. Georgakopoulos, P. Gallos, V.P. Plagianakos, Using Big Data Analytics to Detect Fraud in Healthcare Provision, In: Proceedings of the 2020 IEEE 5th Middle East and Africa Conference on Biomedical Engineering (MECBME2020), 2020.

2019

  1. V.P. Plagianakos, Healthcare Fraud Detection Using Machine Learning Approaches, In: Proceedings of the 2019 ISI World Statistics Congress 2019 (ISI2019), 2019.
  2. A.G. Vrahatis, S.K. Tasoulis, G.N. Dimitrakopoulos, V.P. Plagianakos, Visualizing High-Dimensional Single-Cell RNA-seq Data via Random Projections and Geodesic Distances, In: Proceedings of the 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB2019), 2019.
  3. A.G. Vrahatis, G.N. Dimitrakopoulos, S.K. Tasoulis, V.P. Plagianakos, A Single-Cell Systems Biology Approach for Disease-Specific Subpathway Extraction, In: Proceedings of the 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB2019), 2019.
  4. A.G. Vrahatis, G.N. Dimitrakopoulos, S.K. Tasoulis, V.P. Plagianakos, Enhancing Clustering of Single-Cell RNA-Seq Data by Proximity Learning on Random Projected Spaces, In: Proceedings of the 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE2019), 846-849, 2019.
  5. A.G. Vrahatis, G.N. Dimitrakopoulos, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Single-cell Regulatory Network Inference and Clustering from High-Dimensional Sequencing Data, In: Proceedings of the 2019 IEEE International Conference on Big Data (BigData2019), 2782–2789, 2019.
  6. S.V. Georgakopoulos, V.P. Plagianakos, Efficient Learning Rate Adaptation for Convolutional Neural Network Training, In: Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN2019), 1–8, 2019.
  7. S.V. Georgakopoulos, S.K. Tasoulis, A.G. Vrahatis, V.P. Plagianakos, Convolutional Νeural Νetworks for Τwitter Τext Τoxicity Αnalysis, In: Proceedings of the INNS Big Data and Deep Learning Conference (INNSBDDL2019), 370–379, 2019.
  8. S.K. Tasoulis, G.I. Mallis, S.V. Georgakopoulos, A.G. Vrahatis, V.P. Plagianakos, I. Maglogiannis, Deep learning and change detection for fall recognition, In: Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN 2019), 262-273, 2019.
  9. C. Panagopoulos, A. Menychtas, G. Fouskas, V.P. Plagianakos, I. Maglogiannis, K. Delimpasis, M. Galliakis, D. Petropoulos, C. Gkartzios, C. Koumpoulis, A smart infotainment system equipped with emotional intelligence, In: Proceedings of the 17th International Conference on Informatics, Management and Technology in Healthcare, Studies in Health Technology and Informatics, Vol. 262, 214–217, 2019.

2018

  1. S.K. Tasoulis, A.G. Vrahatis, S.V. Georgakopoulos, V.P. Plagianakos, Biomedical Data Ensemble Classification Using Random Projections, In: Proceedings of the 2018 IEEE International Conference on Big Data (Big Data), 166–172, 2018.
  2. S.K. Tasoulis, A.G. Vrahatis, S.V. Georgakopoulos, V.P. Plagianakos, Visualizing High-Dimensional Single-Cell RNA-Sequencing Data Through Multiple Random Projections, In: Proceedings of the 2018 IEEE International Conference on Big Data (Big Data), 5448–5450, 2018.
  3. S.K. Tasoulis, A.G. Vrahatis, S.V. Georgakopoulos, V.P. Plagianakos, Real Time Sentiment Change Detection of Twitter Data Streams, In: Proceedings of the 2018 Innovations in Intelligent Systems and Applications (INISTA), 1–6, 2018.
  4. S.V. Georgakopoulos, S.K. Tasoulis, A.G. Vrahatis, V.P. Plagianakos, Convolutional Neural Networks for Toxic Comment Classification, In: Proceedings of the 10th Hellenic Conference on Artificial Intelligence (SETN2018), 35:1–35:6, 2018.
  5. G.N. Dimitrakopoulos, A.G. Vrahatis, V.P. Plagianakos, K. Sgarbas, Pathway analysis using XGBoost classification in Biomedical Data, In: Proceedings of the 10th Hellenic Conference on Artificial Intelligence, Vol. 46, 1-6, 2018.
  6. K. Delibasis, I. Maglogiannis, S.V. Georgakopoulos, K. Kottari, V.P. Plagianakos, Assessing Image Analysis Filters as Augmented Input to Convolutional Neural Networks for Image Classification, In: Proceedings of the Artificial Neural Networks and Machine Learning – International Conference on Artificial Neural Networks (ICANN) 2018, 188–196, 2018.

2017

  1. S.V. Georgakopoulos, V.P. Plagianakos, A novel adaptive learning rate algorithm for convolutional neural network training, In: Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN 2017), 327–336, 2017.
  2. S.V. Georgakopoulos, K. Kottari, K. Delibasis, V.P. Plagianakos, I. Maglogiannis, Detection of Malignant Melanomas in Dermoscopic Images Using Convolutional Neural Network with Transfer Learning, In: Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN 2017), 404-414, 2017.

2016

  1. S.V. Georgakopoulos, D.K. Iakovidis, M. Vasilakakis, V.P. Plagianakos, A. Koulaouzidis, Weakly-supervised Convolutional learning for detection of inflammatory gastrointestinal lesions, In: Proceedings of the IEEE International Conference on Imaging Systems and Techniques (IST 2016), 510-514, 2016.
  2. S.V. Georgakopoulos, K. Kottari, K. Delibasis, V.P. Plagianakos, I. Maglogiannis, Convolutional Neural Networks for Pose Recognition in Binary Omni-directional Images, In: Proceedings of the International Conference on Artificial Intelligence Applications and Innovations (AIAI 2016), 106-116, 2016.
  3. K.K. Delibasis, I. Maglogiannis, V. Plagianakos, Silhouette labeling and tracking in calibrated omnidirectional video sequences, In: Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2016), 2016.
  4. K. Kottari, K. Delibasis, V.P. Plagianakos, Real time measurements for quality control of industrial rod manufacturing, In: Proceedings of the IEEE International Conference on Imaging Systems and Techniques (IST 2016), 423-428, 2016.

2015

  1. S.V. Georgakopoulos, S.K. Tasoulis, I. Maglogiannis, V.P. Plagianakos, On-Line Fall Detection via Mobile Accelerometer Data, In: Proceedings of the International Conference on Artificial Intelligence Applications and Innovations (AIAI 2015), 103-112, 2015.
  2. S.V. Georgakopoulos, S.K. Tasoulis, V.P. Plagianakos, Efficient Change Detection for High Dimensional Data Streams, In: Proceedings of the IEEE International Conference on Big Data (Big Data 2015), 2219 - 2222, 2015.
  3. S.V. Georgakopoulos, P. Chrysanthopoulos, D. Chatzis, A. Koulaouzidis, V.P. Plagianakos, D.K. Iakovidis, Towards a Color Space for Automated Lesion Segmentation in Robotic Capsule Endoscopy, In: Proceedings of the Workshop on Robotic Endoscopic Capsules for Gastrointestinal Screening, Diagnosis, and Therapy: Achievements and Future Challenges, IEEE International Conference on Intelligent Robots and Systems (IROS 2015), 2015.

2014

  1. K. Delibasis, V.P. Plagianakos, I. Maglogiannis, Pose Recognition in Indoor Environments using a Fisheye Camera and a Parametric Human Model, In: Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP 2014), Lisbon, Portugal, 2014.
  2. V.P. Plagianakos, Unsupervised Clustering and Multi-Optima Evolutionary Search, In: Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2014), 2014.
  3. K.K. Delibasis, S.V. Georgakopoulos, V.P. Plagianakos, I. Maglogiannis, Calculation of Complex Zernike Moments with Geodesic Correction for Pose Recognition in Omni-directional Images, In: Proceedings of the International Conference on Artificial Intelligence Applications and Innovations (AIAI 2014), 375-384, 2014.
  4. K. Kottari, K. Delibasis, V.P. Plagianakos, I. Maglogiannis, Fish-Eye Camera Video Processing and Trajectory Estimation Using 3D Human Models, In: Proceedings of the International Conference on Artificial Intelligence Applications and Innovations (AIAI 2014), 385-394, 2014.
  5. I. Maglogiannis, V. Pigadas, V.P. Plagianakos, Cloud Based Audio and Video Communication in Personal Health Systems: Voip and Webrtc, In: Proceedings of the European, Mediterranean & Middle Eastern Conference on Information Systems 2014 (EMCIS 2014), 2014.

2013

  1. S. Georgakopoulos, S.K. Tasoulis, V.P. Plagianakos, I. Maglogiannis, Artificial Neural Networks and Principal Components Analysis for Detection of Idiopathic Pulmonary Fibrosis in Microscopy Images, In: Proceedings of the 14th International Conference on Engineering Applications of Neural Networks (EANN 2013), 2013.
  2. V.P. Plagianakos, Multi-Optima Search Using Differential Evolution and Unsupervised Clustering, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2013), Cancun, Mexico, 2013.
  3. K. Delibasis, T. Goudas, V.P. Plagianakos, I. Maglogiannis, Fisheye Camera Modeling for Human Segmentation Refinement in Indoor Videos, In: Proceedings of the 6th ACM International Conference on Pervasive Technologies Related to Assistive Environments (PETRA 2013), 2013.
  4. K. Delibasis, T. Goudas, V.P. Plagianakos, I. Maglogiannis, Real Time Indoor Robot Localization using RGB Video from a Stationary Fisheye Camera, In: Proceedings of the International Conference on Artificial Intelligence Applications and Innovations (AIAI 2013), 245-254, 2013.
  5. K. Delibasis, T. Goudas, V.P. Plagianakos, I. Maglogiannis, Human segmentation and pose recognition in fish-eye video for assistive environments, In: Proceedings of the 13th IEEE International Conference on BioInformatics and BioEngineering (BIBE 2013), 1-5, 2013.

2012

  1. M.G. Epitropakis, D.K. Tasoulis, N.G. Pavlidis, V.P. Plagianakos, M.N. Vrahatis, Tracking Differential Evolution Algorithms: An adaptive approach through multinomial distribution tracking with exponential forgetting, In: Proceedings of the 7th Hellenic Conference on Artificial Intelligence (SETN 2012), 2012.
  2. S.K. Tasoulis, D.K. Tasoulis, V.P. Plagianakos, Clustering of High Dimensional Data Streams, In: Proceedings of the 7th Hellenic Conference on Artificial Intelligence (SETN 2012), Lamia, Greece, 2012.
  3. S.K. Tasoulis, M.G. Epitropakis, V.P. Plagianakos, D.K. Tasoulis, Density Based Projection Pursuit Clustering, In: Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2012), 2012.
  4. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Multimodal Optimization Using Niching Differential Evolution with Index-based Neighborhoods, In: Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2012), 2012.
  5. M.G. Epitropakis, D.K. Tasoulis, N.G. Pavlidis, V.P. Plagianakos, M.N. Vrahatis, Tracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting, In: Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2012), 2012.
  6. S.K. Tasoulis, I. Maglogiannis, V.P. Plagianakos, Unsupervised Detection of Fibrosis in Microscopy Images Using Fractals and Fuzzy c-Means Clustering, In: Proceedings of the International Conference on Artificial Intelligence Applications and Innovations (AIAI 2012), 385-394, 2012.

2011

  1. S.K. Tasoulis, C.N. Doukas, I. Maglogiannis, V.P. Plagianakos, Independent Component Clustering for Skin Lesions Characterization, In: Proceedings of the 12th EANN / 7th AIAI Joint Conferences on Engineering Applications of Neural Networks / Artificial Intelligence Applications and Innovations, 2011.
  2. S.K. Tasoulis, V.P. Plagianakos, D.K. Tasoulis, Independent Component Divisive Clustering of Gene Expression Data, In: Proceedings of the Seventh International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2011), 2011.
  3. S.K. Tasoulis, C.N. Doukas, I. Maglogiannis, V.P. Plagianakos, Statistical Data Mining of Streaming Motion Data for Fall Detection in Assistive Environments, In: Proceedings of the 33rd IEEE International Conference of the Engineering in Medicine and Biology Society (EMBC 2011), 2011.
  4. V. Pigadas, C. Doukas, V.P. Plagianakos, I. Maglogiannis, Enabling Constant Monitoring of Chronic Patient Using Android Smart Phones, In: Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2011), 2011.
  5. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Finding Multiple Global Optima Exploiting Differential Evolution's Niching Capability, In: Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI 2011), 2011.

2010

  1. S.K. Tasoulis, C.N. Doukas, I. Maglogiannis, V.P. Plagianakos, Skin Lesions Characterisation Utilising Clustering Algorithms, In: Proceedings of the 6th Hellenic Conference on Artificial Intelligence (SETN 2010), 2010.
  2. S.K. Tasoulis, D.K. Tasoulis, V.P. Plagianakos, Evolutionary Principal Direction Divisive Partitioning, In: Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2010), 2010.
  3. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution, In: Proceedings of the IEEE World Congress on Computational Intelligence (WCCI 2010), 2010.
  4. S.K. Tasoulis, C.N. Doukas, I. Maglogiannis, V.P. Plagianakos, Classification of Apoptosis Using Advanced Clustering Techniques on Digital Microscopic Images, In: Proceedings of the 32nd IEEE International Conference of the Engineering in Medicine and Biology Society (EMBC 2010), 2010.
  5. S.K. Tasoulis, C.N. Doukas, I. Maglogiannis, V.P. Plagianakos, Classification of Dermatological Images Using Advanced Clustering Techniques, In: Proceedings of the 32nd IEEE International Conference of the Engineering in Medicine and Biology Society (EMBC 2010), 2010.

2009

  1. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Evolutionary Adaptation of the Differential Evolution Control Parameters, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2009), 2009.
  2. S.K. Tasoulis, V.P. Plagianakos, D.K. Tasoulis, Projection Based Clustering of Gene Expression Data, In: Proceedings of the Sixth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2009), Genova, Italy, 2009.

2008

  1. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Balancing the exploration and exploitation capabilities of the Differential Evolution Algorithm, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2008), 2008.
  2. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Non-Monotone Differential Evolution, In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008), 2008.
  3. V.P. Plagianakos, A. Kalioras, S. Bersimis, Interpreting Shewhart Type Control Chart Signals Using Pattern Based Rules and Artificial Intelligence Techniques, In: Proceedings of the European Network for Business and Industrial Statistics 2008, Athens, 2008.

2007

  1. N.G. Pavlidis, E.G. Pavlidis, M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Computational Intelligence Algorithms For Risk-Adjusted Trading Strategies, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2007), 2007.

2006

  1. N.G. Pavlidis, D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Human Designed Vs. Genetically Programmed Differential Evolution Operators, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2006), 1880-1886, 2006.
  2. D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Differential Evolution Algorithms for Finding Predictive Gene Subsets in Microarray Data, In: Proceedings of the 3rd IFIP Conference on Artificial Intelligence Applications & Innovations (AIAI 2006), 2006.
  3. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Higher-Order Neural Networks Training Using Differential Evolution, In: Proceedings of the International Conference of Numerical Analysis and Applied Mathematics, Hersonissos, Crete, Greece, 2006.
  4. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Hardware-Friendly Higher-Order Neural Network Training Using Distributed Differential Evolution, In: Proceedings of the International Conference of Computational Methods in Sciences and Engineering, 2006.

2005

  1. N.G. Pavlidis, D.K. Tasoulis, V.P. Plagianakos, G. Nikiforidis, M.N. Vrahatis, Spiking Neural Network Training Using Evolutionary Algorithms, In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2005), 2005.
  2. V.P. Plagianakos, D.K. Tasoulis, M.N. Vrahatis, Recent Computational Intelligence Techniques for Gene Expression Data Classification, In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2005), Montreal, Canada, 2005.
  3. D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Clustering in Evolutionary Algorithms to Efficiently Compute Simultaneously Local and Global Minima, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005), 2005.
  4. N.G. Pavlidis, D.K. Tasoulis, V.P. Plagianakos, C. Siriopoulos, M.N. Vrahatis, Computational intelligence methods for financial forecasting, In: Proceedings of the IEEE International Conference of Computational Methods in Sciences and Engineering (ICCMSE2005), 2005.
  5. V.P. Plagianakos, D.K. Tasoulis, M.N. Vrahatis, Hybrid dimension reduction approach for gene expression data classification, In: Proceedings of the IEEE International Joint Conference on Neural Networks 2005, Post-Conference Workshop on Computational Intelligence Approaches for the Analysis of Bioinformatics Data, 2005.

2004

  1. D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Unsupervised Clustering of Bioinformatics Data, In: European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems (Eunite 2004), Germany, 47-53, 2004.
  2. D.K. Tasoulis, N.G. Pavlidis, V.P. Plagianakos, M.N. Vrahatis, Parallel Differential Evolution, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2004), 2004.
  3. K.E Parsopoulos, D.K. Tasoulis, N.G. Pavlidis, V.P. Plagianakos, M.N. Vrahatis, Vector Evaluated Differential Evolution for Multiobjective Optimization, In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2004), 2004.
  4. G.D. Magoulas, V.P. Plagianakos, D.K. Tasoulis, M.N. Vrahatis, Tumor detection in colonoscopy using the unsupervised k-windows clustering algorithm and neural networks, In: Proceedings of the Fourth European Symposium on Biomedical Engineering, 2004.
  5. D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Unsupervised cluster analysis in bioinformatics, In: Proceedings of the Fourth European Symposium on Biomedical Engineering, 2004.

2001

  1. K.E. Parsopoulos, V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Stretching technique for obtaining global minimizers through Particle Swarm Optimization, In: Proceedings of the Particle Swarm Optimization Workshop, 22-29, 2001.
  2. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Hybrid Methods Using Evolutionary Algorithms for On-line Training, In: Proceedings of the INNS-IEEE International Joint Conference on Neural Networks (IJCNN’2001), Washington D.C., U.S.A., 2001.
  3. V.P. Plagianakos, G.D. Magoulas, N.K. Nousis, M.N. Vrahatis, PVM-based Training of Large Neural Architectures, In: Proceedings of the INNS-IEEE International Joint Conference on Neural Networks (IJCNN’2001), 2001.
  4. V.P. Plagianakos, G.D. Magoulas, N.K. Nousis, M.N. Vrahatis, Training Multilayer Networks with Discrete Activation Functions, In: Proceedings of the INNS-IEEE International Joint Conference on Neural Networks (IJCNN’2001), Washington D.C., U.S.A., 2001.
  5. V.P. Plagianakos, E. Tzanaki, Chaotic analysis of seismic time series and short term forecasting using neural networks, In: Proceedings of the INNS-IEEE International Joint Conference on Neural Networks (IJCNN’2001), Washington D.C., U.S.A., 2001.
  6. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Tumor detection in colonoscopic images using hybrid methods for on-line neural network training, In: Proceedings of the Neural Networks and Expert Systems in Medicine and HealthCare, 2001.
  7. D.G. Sotiropoulos, V.P. Plagianakos, M.N. Vrahatis, An Evolutionary Algorithm for Minimizing Multimodal Functions, In: Proceedings of the Hellenic European Research on Computer Mathematics and its Applications Conference (HERCMA'2001), 496-500, 2001.
  8. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Improved Neural Network-based Interpretation of Colonoscopy Images Through On-line Learning and Evolution, In: Proceedings of EUNITE 2001 Conference, Tenerife, Spain, 2001.

2000

  1. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Global Learning Rate Adaptation in On-line Neural Network Training, In: Proceedings of the Second International ICSC Symposium on Neural Computation (NC'2000), 2000.
  2. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Development and Convergence Analysis of Training Algorithms with Local Learning Rate Adaptation, In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN’2000), 2000.
  3. V.P. Plagianakos, M.N. Vrahatis, Training Neural Networks with Threshold Activation Functions and Constrained Integer Weights, In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN’2000), 2000.

1999

  1. V.P. Plagianakos, M.N. Vrahatis, Training Neural Networks with 3-bit Integer Weights, In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO’99), W. Banzhaf, J. Daida, A.E. Eiben, M.H. Garzon, V. Honavar, M. Jakiela, R.E. Smith (eds.), 910-915, 1999.
  2. V.P. Plagianakos, M.N. Vrahatis, Neural Network Training with Constrained Integer Weights, In: Proceedings of the Congress of Evolutionary Computation (CEC’99), P.J. Angeline, Z. Michalewicz, M. Schoenauer, X. Yao, A. Zalzala (eds.), 2007-2013, 1999.
  3. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Nonmonotone Learning Rules For Backpropagation Networks, In: Proceedings of the 6th IEEE International Conference on Electronics, Circuits and Systems (ICECS '99), 291-294, 1999.
  4. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Effective Neural Network Training with a Different Learning Rate for each Weight, In: Proceedings of the 6th IEEE International Conference on Electronics, Circuits and Systems (ICECS '99), 591-594, 1999.
  5. G.D. Magoulas, V.P. Plagianakos, M.N. Vrahatis, Sign-methods for Training with Imprecise Error Function and Gradient Values, In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN’99), 1999.
  6. M.N. Vrahatis, G.D. Magoulas, V.P. Plagianakos, Convergence Analysis of the Quickprop Method, In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN’99), 1999.
  7. V.P. Plagianakos, M.N. Vrahatis, G.D. Magoulas, Nonmonotone Methods for Backpropagation Training with Adaptive Learning Rate, In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN’99), 1999.
  8. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Optimization Strategies and Backpropagation Neural Networks, In: Proceedings of the Seventh Hellenic Conference on Informatics, Ioannina, Greece, 1999.

Chapters in Edited Volumes

2024

  1. P. Barmpas, P. Anagnostou, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, HCER: Hierarchical Clustering-Ensemble Regressor, In: Engineering Applications of Neural Networks, L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, C. Jayne (eds.), 369–378, 2024.
  2. P.V. Tsakmaki, S.K. Tasoulis, S.V. Georgakopoulos, V.P. Plagianakos, Machine Learning-driven Improvements in HRV Artifact Correction for Psychosis Prediction in the Schizophrenia Spectrum, In: Engineering Applications of Neural Networks, L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, C. Jayne (eds.), 544–557, 2024.

2022

  1. P.C. Theocharopoulos, A. Tsoukala, S.V. Georgakopoulos, S.K. Tasoulis, V.P. Plagianakos, Text analysis of COVID-19 tweets, In: Engineering Applications of Neural Networks, Lazaros Iliadis, Chrisina Jayne, Anastasios Tefas, Elias Pimenidis (eds.), 517–528, 2022.
  2. I.L. Dallas, A.G. Vrahatis, S.K. Tasoulis, V.P. Plagianakos, Recent Dimensionality Reduction Techniques for High-Dimensional COVID-19 Data, In: Computational Intelligence Methods for Bioinformatics and Biostatistics, D. Chicco, A. Facchiano, E. Tavazzi, E. Longato, M. Vettoretti, A. Bernasconi, S. Avesani, P. Cazzaniga (eds.), 227–241, 2022.

2020

  1. A.G. Vrahatis, S.K. Tasoulis, I. Maglogiannis, V.P. Plagianakos, Recent Machine Learning Approaches for Single-Cell RNA-seq Data Analysis, In: Advanced Computational Intelligence in Healthcare, 65-79, 2020.

2009

  1. M.G. Epitropakis, V.P. Plagianakos, M.N. Vrahatis, Evolutionary Algorithm Training of Higher-Order Neural Networks, In: Artificial Higher Order Neural Networks for Computer Science and Engineering: Tends for Emerging Applications, Ming Zhang (ed.), 2009.

2008

  1. V.P. Plagianakos, D.K. Tasoulis, M.N. Vrahatis, A Review of Major Application Areas of Differential Evolution, In: Advances in Differential Evolution, U.K. Chakraborty (ed.), 197-238, 2008.

2007

  1. D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Computational Intelligence Algorithms and DNA Microarrays, In: Studies in Computational Intelligence (SCI), 2007 (Chapter 1).

2006

  1. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Improved learning of neural nets through global search, In: Global Optimization: Scientific and Engineering Case Studies, Series: Nonconvex Optimization and Its Applications, J.D. Pintér (ed.), Vol. 85, 361-388, 2006 (Chapter 15).

2004

  1. D.K. Tasoulis, L. Vladutu, V.P. Plagianakos, A. Bezerianos, M.N. Vrahatis, On-line Neural Network Training for Automatic Ischemia Episode Detection, In: Lecture Notes in Computer Science (LNAI), Vol. 3070, 1062-1068, 2004.

2003

  1. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, On-line neural network training, In: Order and Chaos in Nonlinear Dynamical Systems, T. Bountis, S. Ichtiaroglou, S. Pnevmatikos (eds.), Vol. 8, 329-340, 2003 (in Greek).

2002

  1. Μ.Ν. Βραχάτης, Β.Π. Πλαγιανάκος, Γ. Μαγουλάς, Εισαγωγή στα Τεχνητά Νευρωνικά Δίκτυα, In: Τάξη και Χάος στα Μη Γραμμικά Συστήματα, Αν. Μπούντης, Δ. Έλληνας, Ι. Γρυσπολάκης (eds.), Vol. 7, 225-247, 2002.

2001

  1. V.P. Plagianakos, M.N. Vrahatis, A Derivative Free Minimization Method For Noisy Functions, In: Advances in Combinatorial and Global Optimization, A. Migdalas, P. Pardalos, R. Burkard (eds.), 283-296, 2001.
  2. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Supervised training using global search methods, In: Advances in Convex Analysis and Global Optimization, Honoring the memory of C. Caratheodory (1873-1950), N. Hadjisavvas, P.M. Pardalos (eds.), 421-432, 2001.
  3. V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Learning rate adaptation in stochastic gradient descent, In: Advances in Convex Analysis and Global Optimization, Honoring the memory of C. Caratheodory (1873-1950), N. Hadjisavvas, P.M. Pardalos (eds.), 433-444, 2001.
  4. K.E. Parsopoulos, V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, Improving the particle swarm optimizer by function “stretching”, In: Advances in Convex Analysis and Global Optimization, Honoring the memory of C. Caratheodory (1873-1950), N. Hadjisavvas, P.M. Pardalos (eds.), 445-457, 2001.
  5. G.D. Magoulas, V.P. Plagianakos, G.S. Androulakis, M.N. Vrahatis, A Framework for the Development of Globally Convergent Adaptive Learning Rate Algorithms, In: Progress in Computer Research, F.H. Columbus (ed.), Vol. II, 2001.

2000

  1. Μ.Ν. Βραχάτης, Γ. Μαγουλάς, Β.Π. Πλαγιανάκος, Η Εκπαίδευση Τεχνητών Νευρωνικών Δικτύων με Επίβλεψη, In: Τάξη και Χάος στα Μη Γραμμικά Συστήματα, Αν. Μπούντης, Σ. Πνευματικός (eds.), Vol. 6, 243-262, 2000.

1999

  1. V.P. Plagianakos, G.D. Magoulas, G.S. Androulakis, M.N. Vrahatis, Global Search Methods for Neural Network Training, In: Advances in Intelligent Systems and Computer Science, N.E. Mastorakis (ed.), 47-52, 1999.
  2. G.D. Magoulas, V.P. Plagianakos, G.S. Androulakis, M.N. Vrahatis, A Framework for the Development of Globally Convergent Adaptive Learning Rate Algorithms, In: Advances in Intelligent Systems and Computer Science, N.E. Mastorakis (ed.), 207-212, 1999.

1998

  1. V.P. Plagianakos, D.G. Sotiropoulos, M.N. Vrahatis, An Improved Backpropagation Method with Adaptive Learning Rate, In: Recent Advances in circuits and systems, N.E. Mastorakis (ed.), 1998.
  2. V.P. Plagianakos, D.G. Sotiropoulos, M.N. Vrahatis, Integer Weight Training by Differential Evolution Algorithms, In: Recent Advances in circuits and systems, N.E. Mastorakis (ed.), 1998.