Publications

Year: 2024

• Georgios Kostopoulos; Gregory Davrazos; Sotiris Kotsiantis. “Explainable Artificial Intelligence-Based Decision Support Systems: A Recent Review.” Electronics 13(14): 2842 (2024). DOI: 10.3390/electronics13142842. [Open Access]
• Pantelis Linardatos; Vasilis Papastefanopoulos; Sotiris Kotsiantis. “Regressor Cascading for Time Series Forecasting.” Intelligent Decision Technologies 18(2): 1139–1156 (2024). DOI: 10.3233/IDT-240224
• Aristidis G. Vrahatis; Konstantinos Lazaros; Sotiris Kotsiantis. “Graph Attention Networks: A Comprehensive Review of Methods and Applications.” Future Internet 16(9): 318 (2024). DOI: 10.3390/fi16090318. [Open Access]

Year: 2023

• Gregory Davrazos; Theodor Panagiotakopoulos; Sotiris Kotsiantis; Achilles Kameas. “IoT Device Identification Using a Meta-Ensemble Multi-Class Classifier.” In Proc. 14th Int’l Conf. on Information, Intelligence, Systems & Applications (IISA 2023), Volos, Greece, 2023. DOI: 10.1109/IISA59645.2023.10345911
• Gregory Davrazos; Theodor Panagiotakopoulos; Sotiris Kotsiantis; Achilles Kameas. “Predicting Cost of Municipal Waste Management Using IoT Data and Machine Learning.” In Proc. 14th Int’l Conf. on Information, Intelligence, Systems & Applications (IISA 2023), Volos, Greece, 2023. DOI: 10.1109/IISA59645.2023.10345856

Year: 2022

• Georgios Kostopoulos; Theodor Panagiotakopoulos; Sotiris Kotsiantis; Christos Pierrakeas; Achilles Kameas. “Interpretable Models for Early Prediction of Certification in MOOCs: A Case Study on a MOOC for Smart City Professionals.” IEEE Access 9: 165881-165891 (2021, published online 2022). DOI: 10.1109/ACCESS.2021.3134787. [Open Access]
• Eleftherios Kouloumpris; Athina Konstantinou; Stamatis Karlos; Grigorios Tsoumakas; Ioannis P. Vlahavas. “Short‑Term Load Forecasting with Clustered Hybrid Models Based on Hour Granularity.” In Proc. 12th Hellenic Conf. on Artificial Intelligence (SETN 2022), Corfu, Greece, 2022. DOI: 10.1145/3533670.3535687
• Vangjel Kazllarof; Sotiris Kotsiantis. “Human Activity Recognition Using Time Series Feature Extraction and Active Learning.” In Proc. 12th Hellenic Conf. on Artificial Intelligence (SETN 2022), Corfu, Greece, 2022

Year: 2021

• Nikos Fazakis; Otilia Kocsis; Elias Dritsas; Sotiris Alexiou; Nikos Fakotakis; Konstantinos Moustakas. “Machine Learning Tools for Long‑Term Type 2 Diabetes Risk Prediction.” IEEE Access 9: 103737-103757 (2021). DOI: 10.1109/ACCESS.2021.3098691. [Open Access]
• Maria Tsiakmaki; Georgios Kostopoulos; Sotiris Kotsiantis; Odysseas Ragos. “Fuzzy‑Based Active Learning for Predicting Student Academic Performance Using AutoML: A Step‑Wise Approach.” Journal of Computing in Higher Education 33(3): 635–667 (2021). DOI: 10.1007/s12528-021-09279-x
• Emmanuel Pintelas; Meletios Liaskos; Ioannis Livieris; Sotiris Kotsiantis; Panagiotis Pintelas. “A Novel Explainable Image Classification Framework: Case Study on Skin Cancer and Plant Disease Prediction.” Neural Computing and Applications 33(22): 15171–15189 (2021). DOI: 10.1007/s00521-021-06141-0
• Athanasios Salamanis; Anastasia-Dimitra Lipitakis; Sotiris Kotsiantis; Dimosthenis Anagnostopoulos; George A. Gravvanis. “An Adaptive Cluster‑Based Sparse Autoregressive Model for Large‑Scale Multi‑Step Traffic Forecasting.” Expert Systems with Applications 180: 115093 (2021). DOI: 10.1016/j.eswa.2021.115093
• Charalampos M. Liapis; Aikaterini Karanikola; Sotiris Kotsiantis. “A Multi‑Method Survey on the Use of Sentiment Analysis in Multivariate Financial Time Series Forecasting.” Entropy 23(12): 1603 (2021). DOI: 10.3390/e23121603. [Open Access]
• Vasileios Papastefanopoulos; Pantelis Linardatos; Sotiris Kotsiantis. “Unsupervised Outlier Detection: A Meta‑Learning Algorithm Based on Feature Selection.” Electronics 10(18): 2236 (2021). DOI: 10.3390/electronics10182236. [Open Access]
• Theodor Panagiotakopoulos; Sotiris Kotsiantis; Georgios Kostopoulos; Omiros Iatrellis; Achilles Kameas. “Early Dropout Prediction in MOOCs through Supervised Learning and Hyperparameter Optimization.” Electronics 10(14): 1701 (2021). DOI: 10.3390/electronics10141701. [Open Access]
• Pantelis Linardatos; Vasileios Papastefanopoulos; Sotiris Kotsiantis. “Explainable AI: A Review of Machine Learning Interpretability Methods.” Entropy 23(1): 18 (2021). DOI: 10.3390/e23010018. [Open Access]
• Nikos Fazakis; Elias Dritsas; Otilia Kocsis; Nikos Fakotakis; Konstantinos Moustakas. “Long‑Term Cholesterol Risk Prediction Using Machine Learning Techniques in ELSA Database.” In Proc. International Joint Conf. on Computational Intelligence (IJCCI 2021), Volume 2, pp. 445–450 (2021). DOI: 10.5220/0010727200003063
• Elias Dritsas; Nikos Fazakis; Otilia Kocsis; Konstantinos Moustakas; Nikos Fakotakis. “Optimal Team Pairing of Elder Office Employees with Machine Learning on Synthetic Data.” In Proc. 12th Int’l Conf. on Information, Intelligence, Systems & Applications (IISA 2021), Chania, Greece, pp. 1–4 (2021). DOI: 10.1109/IISA52424.2021.9555522

Year: 2020

• Christos K. Aridas, Stamatis Karlos, Vasileios G. Kanas, Nikos Fazakis, Sotiris B. Kotsiantis:
  Uncertainty Based Under-Sampling for Learning Naive Bayes Classifiers Under Imbalanced Data Sets. In IEEE Access 8: 2122-2133 (2020); DOI: 10.1109/ACCESS.2019.2961784 [link] – Open Access (Funded by ELIDEK)

• Stamatis Karlos, Georgios Kostopoulos, Sotiris Kotsiantis: A Soft-Voting Ensemble Based Co-Training Scheme Using Static Selection for Binary Classification Problems. In Algorithms 13(1): 26 (2020); DOI: 10.3390/a13010026 [link] – Open Acsess

• Nikos Fazakis, Georgios Kostopoulos, Sotiris Kotsiantis, Iosif Mporas: Iterative Robust Semi-Supervised Missing Data Imputation. IEEE Access 8: 90555-90569 (2020); DOI: 10.1109/ACCESS.2020.2994033 [link] – Open Access

• Nikos Fazakis, Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas: An active learning ensemble method for regression tasks. Intell. Data Anal. 24(3): 607-623 (2020); DOI: 10.3233/IDA-194608 [link]

Year: 2019

• Georgios Kostopoulos, Sotiris Kotsiantis, Nikos Fazakis, Giannis Koutsonikos, Christos Pierrakeas:
  A Semi-Supervised Regression Algorithm for Grade Prediction of Students in Distance Learning Courses. International Journal on Artificial Intelligence Tools 28(4): 1940001:1-1940001:19 (2019)

• Nikos Fazakis, Vasileios G. Kanas, Christos Aridas, Stamatis Karlos, Sotiris Kotsiantis: Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme. In Entropy 2019, 21(10), 988; DOI: https://doi.org/10.3390/e21100988 [link] – Open Access (Funded by ELIDEK)

• Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas: A multi-scheme semi-supervised regression approach. Pattern Recognition Letters 125: 758-765 (2019), DOI: 10.1016/j.patrec.2019.07.022 [link]

• Stamatis Karlos, Vasileios G. Kanas, Nikos Fazakis, Christos Aridas, Sotiris Kotsiantis: Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme. In: MacIntyre J., Maglogiannis I., Iliadis L., Pimenidis E. (eds) Artificial Intelligence Applications and Innovations. AIAI 2019. IFIP Advances in Information and Communication Technology, vol 559. Springer, Cham, ISBN: 978-1-4503-6610-6, DOI: 10.1007/978-3-030-19823-7_3 [link] [code] (Funded by ELIDEK)

• Vangjel Kazllarof, Stamatis Karlos and Sotiris Kotsiantis S. (2019) Active learning Rotation Forest for multiclass classification. In: Computational Intelligence Journal, Wiley (COIN). DOI: 10.1111/coin.12217 [link]

• Georgios Kostopoulos, Stamatis Karlos and Sotiris Kotsiantis S. (2019) Multi-view Learning for Early Prognosis of Academic Performance: A Case Study. In: IEEE Transactions on Learning Technologies. DOI: 10.1109/TLT.2019.2911581 [link] [code]

• Nikos Fazakis, Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas: Self-trained eXtreme Gradient Boosting Trees. IISA 2019: 1-6

• Stamatis Karlos, Vasileios G. Kanas, Christos K. Aridas, Nikos Fazakis, Sotiris Kotsiantis:
  Combining Active Learning with Self-train algorithm for classification of multimodal problems. IISA 2019: 1-8 – Best student paper award (Funded by ELIDEK)

• Georgios Kostopoulos, Nikos Fazakis, Sotiris Kotsiantis, Kyriakos N. Sgarbas:
  Multi-objective Optimization of C4.5 Decision Tree for Predicting Student Academic Performance. IISA 2019: 1-4

Year: 2018

• Aikaterini Karanikola, Stamatis Karlos, Vangjel Kazllarof, Sotiris Kotsiantis: An incrementally updateable ensemble learner, Proceedings of the 22nd Pan-Hellenic Conference on Informatics, PCI2018, Article No. 31, Athens, Greece — November 29 – December 01, ACM 2018, ISBN: 978-1-4503-6610-6, DOI: 10.1145/3291533.3291536 [link]

• Karlos S., Kaleris K., Fazakis N., Kanas V.G., Kotsiantis S. (2018) Optimized Active Learning Strategy for Audiovisual Speaker Recognition. In: Karpov A., Jokisch O., Potapova R. (eds) Speech and Computer. SPECOM 2018. Lecture Notes in Computer Science, vol 11096. Springer, Cham. pp 281-290, DOI: 10.1007/978-3-319-99579-3_30 [link]

• Kostopoulos, Georgios, Karlos, Stamatis, Kotsiantis, Sotiris and Ragos, Omiros: Semi-supervised regression: A recent review,  Journal of Intelligent & Fuzzy Systems 35(2): 1483-1500 (2018) [link]

• Stamatis Karlos, Nikos Fazakis, Konstantinos Kaleris, Vasileios G. Kanas and Sotos Kotsiantis: An incremental self-trained ensemble algorithm, 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018), ISBN: 978-1-5386-1376-4, DOI:  10.1109/EAIS.2018.8397180 [link] [pdf]

• Aikaterini Karanikola, Stamatis Karlos, Vangjel Kazllarof, Eirini Kateri and Sotos Kotsiantis: Active Fuzzy Rule Induction , 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018), ISBN: 978-1-5386-1376-4, DOI:  10.1109/EAIS.2018.8397175 [link]

• Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis and Kyriakos Sgarbas: A Semi-supervised regressor based on model trees – SETN ’18, July 9–15, 2018, Rio Patras, Greece, ACM ISBN: 978-1-4503-6433-1/18/07, DOI: 10.1145/3200947.3201033

• Stamatis Karlos, Aikaterini Karanikola, Vangjel Kazllarof and Sotiris Kotsiantis: Local weighted Averaged 2-Dependence Estimator – SETN ’18, July 9–15, 2018, Rio Patras, Greece, ACM ISBN: 978-1-4503-6433-1/18/07, DOI: 10.1145/3200947.3201047

Year: 2017

• Vangjel Kazllarof, Stamatis Karlos, Sotiris Kotsiantis and Michalis Xenos: Automated hand gesture recognition exploiting Active Learning methods, Proceedings of the 21st Pan-Hellenic Conference on Informatics, PCI2017, Article No. 3, Larissa, Greece — September 28 – 30, ACM 2017, ISBN: 978-1-4503-5355-7 [link]

• Ioannis Livieris, Stamatis Karlos, Vassilis Tampakas and Panagiotis Pintelas: A hybrid conjugate gradient method based on the self-scaled memoryless BFGS update, Proceedings of the 21st Pan-Hellenic Conference on Informatics, PCI2017, Article No. 21, Larissa, Greece — September 28 – 30, ACM 2017, ISBN: 978-1-4503-5355-7 [link]

• Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis and Kyriakos Sgarbas: An Empirical Study of Active Learning for Text
  Classification, KES International Conference on Knowledge Based and Intelligent Engineering Information
  & Engineering Systems (KES2017 – CIMA2017) [link]

• Vasileios Papastefanopoulos, Stamatis Karlos and Sotiris Kotsiantis: Using Semi-Supervised Learning Methods for Credit
  Score Problem,  KES International Conference on Knowledge Based and Intelligent Engineering Information
  & Engineering Systems (KES2017 –  CIMA2017) [link]

• Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Vassilis Tampakas: Evaluating Active Learning Methods for Bankruptcy Prediction, BFAL2017: 57-66

• Georgios Kostopoulos, Sotiris Kotsiantis, Vassilios S. Verykios: A Prognosis of Junior High School Students’ Performance Based on Active Learning Methods. BFAL2017: 67-76

• Stamatis Karlos, George Kostopoulos, Sotiris Kotsiantis, Vasilis Tampakas: Using Active Learning Methods for predicting fraudulent financial statements, EANN 2017: 351-362 [link]

• Georgios Kostopoulos, Anastasia-Dimitra Lipitakis, Sotiris Kotsiantis, George Gravvanis: Predicting Student Performance in Distance Higher Education Using Active Learning, EANN2017: 75-86 [link]

• Kostopoulos, G., Kotsiantis, S., Ragos, O., & Grapsa, T., Early Dropout Prediction in Distance Higher Education Using Active Learning, IISA2017 

• Kostopoulos, G., Livieris, I., Kotsiantis, S., & Tampakas, V., Enhancing High School Students’ Performance based on Semi-Supervised Methods, IISA2017

• Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis, Kyriakos N. Sgarbas: “Self-Trained Stacking Model for Semi-Supervised Learning”, International Journal on Artificial Intelligence Tools 26(2): 1-21 (2017), DOI: 10.1142/S0218213017500014 [link] [results]

• G Kamaris, S Karlos, S Terpinas, D koutsaidis, J Mourjopoulos: Audio System Spatial Image Evaluation via Binaural Feature Classification, Audio Engineering Society Convention 142, Berlin (AES Engineering Briefs). [link] [link]

• Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, and Kyriakos Sgarbas, “Self-trained Rotation Forest for semi-supervised learning”, Journal of Intelligent and Fuzzy Systems 32(1): 711-722 (2017), DOI: 10.3233/JIFS-152641. [link] [results]

• Stamatis Karlos, Nikos Fazakis, Angeliki-Panagiota Panagopoulou, Sotiris B. Kotsiantis, Kyriakos Sgarbas: “Locally application of naive Bayes for self-training”, Evolving Systems, March 2017, Volume 8, Issue 1, pp. 1-16, DOI: 10.1007/s12530-016-9159-3. [link] [view-only-version] [results]

Year: 2016

• Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis, and Kyriakos Sgarbas: Semi-supervised forecasting of fraudulent financial statements, Proceedings of the 20th Panhellenic Conference on Informatics, PCI 2016, Article No. 34, Patras, Greece, November 10-12, 2016. ACM 2016, ISBN 978-1-4503-4789-1. [link] – Best Student Paper Award

• Vangjel Kazlarof, Stamatis Karlos, Angeliki-Panagiota Panagopoulou, Sotiris Kotsiantis:  Automated hand gesture recognition for educational applications, Proceedings of the 20th Panhellenic Conference on Informatics, PCI 2016, Article No. 20, Patras, Greece, November 10-12, 2016. ACM 2016, ISBN  978-1-4503-4789-1. [link]

• Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, and Kyriakos Sgarbas: Self-labeled Hidden Naive Bayes algorithm for semi-supervised classification, 7th International Conference on Information, Intelligence, Systems & Applications (IISA), 2016, DOI: 10.1109/IISA.2016.7785414. [link] [results][.pdf] [html] – Best Student Paper Award

• Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis, and Kyriakos Sgarbas: Effectiveness of semi-supervised learning in bankruptcy prediction, 7th International Conference on Information, Intelligence, Systems & Applications (IISA), 2016, DOI: 10.1109/IISA.2016.7785435. [link] [.pdf] [html]

• Stamatis Karlos, Nikos Fazakis, Katerina Karanikola, Sotiris Kotsiantis, and Kyriakos Sgarbas: Speech Recognition Combining MFCCs and Image Features, SPECOM 2016: Chapter Speech and Computer, Volume 9811 of the series Lecture Notes in Computer Science pp. 651-658. [link]

• G Kamaris, S Karlos, N Fazakis, S Terpinas, J Mourjopoulos: Binaural Auditory Feature Classification for Stereo Image Evaluation in Listening Rooms, Audio Engineering Society Convention 140, Paris (AES Engineering Briefs). [link] [.pdf]

• Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis, and Kyriakos Sgarbas, “A Semisupervised Cascade Classification Algorithm”, Applied Computational Intelligence and Soft Computing, vol. 2016, Article ID 5919717, 14 pages, 2016. DOI: 10.1155/2016/5919717. [link] [results]

• Nikos Fazakis, Stamatis Karlos, Sotiris Kotsiantis, and Kyriakos Sgarbas, “Self-Trained LMT for Semisupervised Learning”, Computational Intelligence and Neuroscience, vol. 2016, Article ID 3057481, 13 pages, 2016. DOI: 10.1155/2016/3057481. [link] [results]

Year: 2015

• Stamatis Karlos, Nikos Fazakis, Sotiris B. Kotsiantis, Kyriakos Sgarbas:
  Self-Train LogitBoost for Semi-supervised Learning, EANN 2015: Chapter Engineering Applications of Neural Networks Volume 517 of the series Communications in Computer and Information Science pp 139-148. [link] [.pdf]

• Nikos Fazakis, Stamatis Karlos, Sotiris B. Kotsiantis, Kyriakos Sgarbas:
  Speaker Identification Using Semi-supervised Learning, SPECOM 2015: Chapter Speech and Computer, Volume 9319 of the series Lecture Notes in Computer Science pp. 389-396. [link] [.pdf]

• G. Kostopoulos, S. Kotsiantis, P. Pintelas, Predicting Student Performance in Distance Higher Education Using Semi-Supervised Techniques, MEDI 2015, Volume 9344 of the series Lecture Notes in Computer Science pp 259-270, 2015. [link]
  

• G. Kostopoulos, S. Kotsiantis, P. Pintelas. 2015. Estimating student dropout in distance higher education using semi-supervised techniques. In Proceedings of the 19th Panhellenic Conference on Informatics (PCI ’15), ACM, 38-43. [link]