Semi-supervised regression: A recent review G Kostopoulos, S Karlos, S Kotsiantis, O Ragos Journal of Intelligent & Fuzzy Systems 35 (2), 1483-1500, 2018 | 154 | 2018 |
ETHOS: a multi-label hate speech detection dataset I Mollas, Z Chrysopoulou, S Karlos, G Tsoumakas Complex & Intelligent Systems 8 (6), 4663-4678, 2022 | 98 | 2022 |
Ethos: an online hate speech detection dataset I Mollas, Z Chrysopoulou, S Karlos, G Tsoumakas arXiv preprint arXiv:2006.08328, 2020 | 91 | 2020 |
Uncertainty based under-sampling for learning naive bayes classifiers under imbalanced data sets CK Aridas, S Karlos, VG Kanas, N Fazakis, SB Kotsiantis IEEE Access 8, 2122-2133, 2019 | 69 | 2019 |
A soft-voting ensemble based co-training scheme using static selection for binary classification problems S Karlos, G Kostopoulos, S Kotsiantis Algorithms 13 (1), 26, 2020 | 58 | 2020 |
Self‐Trained LMT for Semisupervised Learning N Fazakis, S Karlos, S Kotsiantis, K Sgarbas Computational intelligence and neuroscience 2016 (1), 3057481, 2016 | 43 | 2016 |
Multiview learning for early prognosis of academic performance: a case study G Kostopoulos, S Karlos, S Kotsiantis IEEE Transactions on Learning Technologies 12 (2), 212-224, 2019 | 41 | 2019 |
Predicting and Interpreting Students’ Grades in Distance Higher Education through a Semi-Regression Method SK Stamatis Karlos, Georgios Kostopoulos Applied Sciences 10 (23), 8413, 2020 | 40 | 2020 |
Combination of active learning and semi-supervised learning under a self-training scheme N Fazakis, VG Kanas, CK Aridas, S Karlos, S Kotsiantis Entropy 21 (10), 988, 2019 | 20 | 2019 |
A multi-scheme semi-supervised regression approach N Fazakis, S Karlos, S Kotsiantis, K Sgarbas Pattern Recognition Letters 125, 758-765, 2019 | 20 | 2019 |
Short-term renewable energy forecasting in greece using prophet decomposition and tree-based ensembles A Vartholomaios, S Karlos, E Kouloumpris, G Tsoumakas International Conference on Database and Expert Systems Applications, 227-238, 2021 | 15 | 2021 |
Active learning Rotation Forest for multiclass classification V Kazllarof, S Karlos, S Kotsiantis Computational Intelligence 35 (4), 891-918, 2019 | 15 | 2019 |
Classification of acoustical signals by combining active learning strategies with semi-supervised learning schemes S Karlos, C Aridas, VG Kanas, S Kotsiantis Neural Computing and Applications, 1-18, 2023 | 14 | 2023 |
Combining active learning with self-train algorithm for classification of multimodal problems S Karlos, VG Kanas, C Aridas, N Fazakis, S Kotsiantis 2019 10th International Conference on Information, Intelligence, Systems and …, 2019 | 14 | 2019 |
Speaker identification using semi-supervised learning N Fazakis, S Karlos, S Kotsiantis, K Sgarbas Speech and Computer: 17th International Conference, SPECOM 2015, Athens …, 2015 | 13 | 2015 |
Locally application of naive Bayes for self-training S Karlos, N Fazakis, AP Panagopoulou, S Kotsiantis, K Sgarbas Evolving Systems 8, 3-18, 2017 | 12 | 2017 |
Self-trained rotation forest for semi-supervised learning N Fazakis, S Karlos, S Kotsiantis, K Sgarbas Journal of Intelligent & Fuzzy Systems 32 (1), 711-722, 2017 | 12 | 2017 |
Effectiveness of semi-supervised learning in bankruptcy prediction S Karlos, S Kotsiantis, N Fazakis, K Sgarbas 2016 7th International Conference on Information, Intelligence, Systems …, 2016 | 12 | 2016 |
Evaluating active learning methods for bankruptcy prediction G Kostopoulos, S Karlos, S Kotsiantis, V Tampakas Brain Function Assessment in Learning: First International Conference, BFAL …, 2017 | 11 | 2017 |
Using active learning methods for predicting fraudulent financial statements S Karlos, G Kostopoulos, S Kotsiantis, V Tampakas Engineering Applications of Neural Networks: 18th International Conference …, 2017 | 11 | 2017 |