Sotiris Kotsiantis

发表

Semi-supervised regression: A recent review

Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, 2018, J. Intell. Fuzzy Syst..

Enhancing high school students' performance based on semi-supervised methods

Georgios Kostopoulos, Ioannis E. Livieris, Sotiris Kotsiantis, 2017, 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA).

Measuring Engagement to Assess Performance of Students in Distance Learning

Vassilios S. Verykios, Sotiris Kotsiantis, Andreas F. Gkontzis, 2018, 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA).

Evaluating Active Learning Methods for Bankruptcy Prediction

Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, 2017, BFAL.

Predicting University Students' Grades Based on Previous Academic Achievements

Georgios Kostopoulos, Christos Pierrakeas, Sotiris Kotsiantis, 2018, 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA).

Implementing AutoML in Educational Data Mining for Prediction Tasks

Georgios Kostopoulos, Sotiris Kotsiantis, O. Ragos, 2019, Applied Sciences.

An incrementally updateable ensemble learner

Stamatis Karlos, Sotiris Kotsiantis, Aikaterini Karanikola, 2018, PCI.

Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme

Nikos Fazakis, Vasileios G. Kanas, Stamatis Karlos, 2019, Entropy.

Self-labeled Hidden Naive Bayes algorithm for semi-supervised classification

Nikos Fazakis, Kyriakos N. Sgarbas, Stamatis Karlos, 2016, 2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA).

Investigation of Combining Logitboost(M5P) under Active Learning Classification Tasks

Stamatis Karlos, Sotiris Kotsiantis, Vangjel Kazllarof, 2020 .

Evaluating and recommending Greek newspapers' websites using clustering

Dimitris Kanellopoulos, Sotiris Kotsiantis, S. Kotsiantis, 2012, Program.

COVID-19: A Comparison of Time Series Methods to Forecast Percentage of Active Cases per Population

Sotiris Kotsiantis, Vasilis Papastefanopoulos, Pantelis Linardatos, 2020, Applied Sciences.

Using Active Learning Methods for Predicting Fraudulent Financial Statements

Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, 2017, EANN.

Combining random forest and support vector machines for semi-supervised learning

Sotiris Kotsiantis, Christos K. Aridas, Christos Aridas, 2015, Panhellenic Conference on Informatics.

Combining ensembles algorithms of symbolic learners

Sotiris Kotsiantis, Anastasia-Dimitra Lipitakis, S. Kotsiantis, 2015, 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA).

Transfer Learning from Deep Neural Networks for Predicting Student Performance

Georgios Kostopoulos, Sotiris Kotsiantis, Omiros Ragos, 2020, Applied Sciences.

A Prognosis of Junior High School Students' Performance Based on Active Learning Methods

Georgios Kostopoulos, Vassilios S. Verykios, Sotiris Kotsiantis, 2017, BFAL.

Optimized Active Learning Strategy for Audiovisual Speaker Recognition

Nikos Fazakis, Vasileios G. Kanas, Stamatis Karlos, 2018, SPECOM.

Machine learning and nonlinear models for the estimation of fundamental period of vibration of masonry infilled RC frame structures

Sotiris Kotsiantis, George C. Tsiatas, Aristotelis E. Charalampakis, 2020 .

Automated hand gesture recognition exploiting Active Learning methods

Michalis Nik Xenos, Stamatis Karlos, Sotiris Kotsiantis, 2017, PCI.

Active fuzzy rule induction

Stamatis Karlos, Sotiris Kotsiantis, Aikaterini Karanikola, 2018, 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students

George A. Gravvanis, Michalis Nik Xenos, Christos Pierrakeas, 2020, Machine Learning Paradigms.

An effective LA approach to predict student achievement

Vassilios S. Verykios, Sotiris Kotsiantis, Andreas F. Gkontzis, 2018, PCI.

An incremental self-trained ensemble algorithm

Nikos Fazakis, Vasileios G. Kanas, Stamatis Karlos, 2018, 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).

Local weighted Averaged 2-Dependence Estimator

Stamatis Karlos, Sotiris Kotsiantis, Aikaterini Karanikola, 2018, SETN.

A predictive analytics framework as a countermeasure for attrition of students

Vassilios S. Verykios, Sotiris Kotsiantis, Christos Panagiotakopoulos, 2019 .

A multi-scheme semi-supervised regression approach

Nikos Fazakis, Kyriakos N. Sgarbas, Stamatis Karlos, 2019, Pattern Recognit. Lett..

Bitcoin Price Prediction Combining Data and Text Mining

Sotiris Kotsiantis, Pantelis Linardatos, S. Kotsiantis, 2020 .

Effectiveness of semi-supervised learning in bankruptcy prediction

Nikos Fazakis, Kyriakos N. Sgarbas, Stamatis Karlos, 2016, 2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA).

A Soft-Voting Ensemble Based Co-Training Scheme Using Static Selection for Binary Classification Problems

Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, 2020, Algorithms.

Early dropout prediction in distance higher education using active learning

Georgios Kostopoulos, Sotiris Kotsiantis, Omiros Ragos, 2017, 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA).

A Semi-Supervised Regression Algorithm for Grade Prediction of Students in Distance Learning Courses

Georgios Kostopoulos, Nikos Fazakis, Sotiris Kotsiantis, 2019, Int. J. Artif. Intell. Tools.

Locally application of naive Bayes for self-training

Nikos Fazakis, Kyriakos N. Sgarbas, Stamatis Karlos, 2017, Evol. Syst..

Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme

Nikos Fazakis, Vasileios G. Kanas, Stamatis Karlos, 2019, AIAI.

A Semi-supervised regressor based on model trees

Nikos Fazakis, Kyriakos N. Sgarbas, Stamatis Karlos, 2018, SETN.

A hybrid method for missing value imputation

Sotiris Kotsiantis, Aikaterini Karanikola, 2019, PCI.

A hybrid Machine Learning methodology for imbalanced datasets

Sotiris Kotsiantis, Anastasia-Dimitra Lipitakis, S. Kotsiantis, 2014, IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications.

Students' evaluation of tutors in distance education: a quasi-longitudinal study

Michalis Nik Xenos, Nikolaos K. Tselios, Sotiris Kotsiantis, 2017, Int. J. Learn. Technol..

Deep Dense Neural Network for Early Prediction of Failure-Prone Students

Georgios Kostopoulos, Sotiris Kotsiantis, Omiros Ragos, 2020 .

Self-Trained Stacking Model for Semi-Supervised Learning

Nikos Fazakis, Kyriakos N. Sgarbas, Stamatis Karlos, 2017, Int. J. Artif. Intell. Tools.

Automated hand gesture recognition for educational applications

Stamatis Karlos, Sotiris Kotsiantis, Vangjel Kazllarof, 2016, PCI.

Integrating global and local boosting

Michael N. Vrahatis, Sotiris Kotsiantis, Anastasia-Dimitra Lipitakis, 2015, 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA).

Predicting Student Performance in Distance Higher Education Using Active Learning

George A. Gravvanis, Georgios Kostopoulos, Sotiris Kotsiantis, 2017, EANN.

Forecasting students' success in an open university

George A. Gravvanis, Christos Pierrakeas, Sotiris Kotsiantis, 2018, Int. J. Learn. Technol..

Semi-supervised forecasting of fraudulent financial statements

Nikos Fazakis, Kyriakos N. Sgarbas, Stamatis Karlos, 2016, PCI.