| Imitation learning: A survey of learning methods A Hussein, MM Gaber, E Elyan, C Jayne ACM Computing Surveys (CSUR) 50 (2), 1-35, 2017 | 1920 | 2017 |
| Mining data streams: a review MM Gaber, A Zaslavsky, S Krishnaswamy ACM Sigmod Record 34 (2), 18-26, 2005 | 1434 | 2005 |
| Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network A Abbas, MM Abdelsamea, MM Gaber Applied Intelligence 51 (2), 854-864, 2021 | 1337 | 2021 |
| Random forests: from early developments to recent advancements K Fawagreh, MM Gaber, E Elyan Systems Science & Control Engineering: An Open Access Journal 2 (1), 602-609, 2014 | 972 | 2014 |
| Learning from data streams: processing techniques in sensor networks J Gama, MM Gaber Springer Science & Business Media, 2007 | 367 | 2007 |
| A survey of data mining techniques for social media analysis M Adedoyin-Olowe, MM Gaber, F Stahl Journal of Data Mining & Digital Humanities 2014, 2014 | 244* | 2014 |
| SA-E: sentiment analysis for education N Altrabsheh, MM Gaber, M Cocea Intelligent Decision Technologies, 353-362, 2013 | 168 | 2013 |
| Detrac: Transfer learning of class decomposed medical images in convolutional neural networks A Abbas, MM Abdelsamea, MM Gaber IEEE Access 8, 74901-74913, 2020 | 160 | 2020 |
| Adaptive mobile activity recognition system with evolving data streams ZS Abdallah, MM Gaber, B Srinivasan, S Krishnaswamy Neurocomputing 150, 304-317, 2015 | 156 | 2015 |
| Edge machine learning: Enabling smart internet of things applications MT Yazici, S Basurra, MM Gaber Big data and cognitive computing 2 (3), 26, 2018 | 151 | 2018 |
| Advances in data stream mining MM Gaber Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2 (1 …, 2012 | 148 | 2012 |
| A survey of classification methods in data streams MM Gaber, A Zaslavsky, S Krishnaswamy Data Streams: models and algorithms, 39-59, 2007 | 146 | 2007 |
| Next challenges for adaptive learning systems I Zliobaite, A Bifet, M Gaber, B Gabrys, J Gama, L Minku, K Musial ACM SIGKDD Explorations Newsletter 14 (1), 48-55, 2012 | 139 | 2012 |
| Activity recognition with evolving data streams: A review ZS Abdallah, MM Gaber, B Srinivasan, S Krishnaswamy ACM Computing Surveys (CSUR) 51 (4), 1-36, 2018 | 136 | 2018 |
| CHIRPS: Explaining random forest classification J Hatwell, MM Gaber, RMA Azad Artificial Intelligence Review 53 (8), 5747-5788, 2020 | 124 | 2020 |
| A framework for resource-aware knowledge discovery in data streams: a holistic approach with its application to clustering MM Gaber, PS Yu Proceedings of the 2006 ACM symposium on Applied computing, 649-656, 2006 | 114 | 2006 |
| Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences J Hatwell, MM Gaber, RM Atif Azad BMC Medical Informatics and Decision Making 20 (1), 250, 2020 | 112 | 2020 |
| A genetic algorithm approach to optimising random forests applied to class engineered data E Elyan, MM Gaber Information sciences 384, 220-234, 2017 | 105 | 2017 |
| A rule dynamics approach to event detection in twitter with its application to sports and politics M Adedoyin-Olowe, MM Gaber, CM Dancausa, F Stahl, JB Gomes Expert Systems with Applications 55, 351-360, 2016 | 100 | 2016 |
| 4S-DT: Self-supervised super sample decomposition for transfer learning with application to COVID-19 detection A Abbas, MM Abdelsamea, MM Gaber IEEE Transactions on Neural Networks and Learning Systems 32 (7), 2798-2808, 2021 | 97 | 2021 |
Shonali KrishnaswamyMonash UniversityVerified email at i2r.a-star.edu.sg
