| Label-noise robust logistic regression and its applications J Bootkrajang, A Kabán Joint European conference on machine learning and knowledge discovery in …, 2012 | 154 | 2012 |
| Towards large scale continuous EDA: a random matrix theory perspective A Kabán, J Bootkrajang, RJ Durrant Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013 | 81 | 2013 |
| Learning kernel logistic regression in the presence of class label noise J Bootkrajang, A Kabán Pattern Recognition 47 (11), 3641-3655, 2014 | 55 | 2014 |
| Classification of mislabelled microarrays using robust sparse logistic regression J Bootkrajang, A Kabán Bioinformatics 29 (7), 870-877, 2013 | 50 | 2013 |
| A generalised label noise model for classification in the presence of annotation errors J Bootkrajang Neurocomputing 192, 61-71, 2016 | 44 | 2016 |
| Boosting in the presence of label noise J Bootkrajang, A Kabán arXiv preprint arXiv:1309.6818, 2013 | 41 | 2013 |
| Multi-class classification in the presence of labelling errors. J Bootkrajang, A Kabán ESANN, 345-350, 2011 | 31 | 2011 |
| Towards instance-dependent label noise-tolerant classification: a probabilistic approach J Bootkrajang, J Chaijaruwanich Pattern Analysis and Applications 23, 95-111, 2020 | 24 | 2020 |
| Recognition of similar characters using gradient features of discriminative regions P Inkeaw, J Bootkrajang, S Marukatat, T Gonçalves, J Chaijaruwanich Expert Systems with Applications 134, 120-137, 2019 | 16 | 2019 |
| Recognition-based character segmentation for multi-level writing style P Inkeaw, J Bootkrajang, P Charoenkwan, S Marukatat, SY Ho, ... International Journal on Document Analysis and Recognition (IJDAR) 21, 21-39, 2018 | 16 | 2018 |
| Learning a label-noise robust logistic regression: Analysis and experiments J Bootkrajang, A Kabán Intelligent Data Engineering and Automated Learning–IDEAL 2013: 14th …, 2013 | 13 | 2013 |
| Orchid classification using homogeneous ensemble of small deep convolutional neural network W Sarachai, J Bootkrajang, J Chaijaruwanich, S Somhom Machine Vision and Applications 33 (1), 17, 2022 | 9 | 2022 |
| Evolutionary hypernetwork classifiers for protein-protein interaction sentence filtering J Bootkrajang, S Kim, BT Zhang Proceedings of the 11th Annual conference on Genetic and evolutionary …, 2009 | 8 | 2009 |
| Towards an improved label noise proportion estimation in small data: a Bayesian approach J Bootkrajang, J Chaijaruwanich International Journal of Machine Learning and Cybernetics 13 (4), 851-867, 2022 | 7 | 2022 |
| A system to estimate the amount and calories of food that elderly people in the hospital consume P Ruenin, J Bootkrajang, J Chawachat Proceedings of the 11th International Conference on Advances in Information …, 2020 | 7 | 2020 |
| Orchids classification using spatial transformer network with adaptive scaling W Sarachai, J Bootkrajang, J Chaijaruwanich, S Somhom Intelligent Data Engineering and Automated Learning–IDEAL 2019: 20th …, 2019 | 6 | 2019 |
| Using Latent Dirichlet Allocation to investigate guest experience in Airbnb accommodation during COVID-19 pandemic in the United Kingdom N Keawtoomla, A Pongwat, J Bootkrajang 2022 19th International joint conference on computer science and software …, 2022 | 5 | 2022 |
| Bus arrival time estimation for public transportation system using LSTM K Panyo, J Bootkrajang, P Inkeaw, J Chaijaruwanich 2020-5th International Conference on Information Technology (InCIT), 134-138, 2020 | 5 | 2020 |
| A generalised label noise model for classification. J Bootkrajang ESANN, 2015 | 5 | 2015 |
| Supervised learning with random labelling errors J Bootkrajang University of Birmingham, 2013 | 3 | 2013 |
Ata KabanUniversity of Birmingham, School of Computer ScienceVerified email at bham.ac.uk
