| Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ... Journal of medical Internet research 18 (12), e323, 2016 | 884 | 2016 |
| Detecting selective forwarding attacks in wireless sensor networks using support vector machines S Kaplantzis, A Shilton, N Mani, YA Sekercioglu 2007 3rd International conference on intelligent sensors, sensor networks …, 2007 | 294 | 2007 |
| Incremental training of support vector machines A Shilton, M Palaniswami, D Ralph, AC Tsoi IEEE transactions on neural networks 16 (1), 114-131, 2005 | 263 | 2005 |
| High dimensional Bayesian optimization using dropout C Li, S Gupta, S Rana, V Nguyen, S Venkatesh, A Shilton arXiv preprint arXiv:1802.05400, 2018 | 162 | 2018 |
| Multi-objective Bayesian optimisation with preferences over objectives M Abdolshah, A Shilton, S Rana, S Gupta, S Venkatesh Advances in neural information processing systems 32, 2019 | 76 | 2019 |
| Bayesian optimization for categorical and category-specific continuous inputs D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5256-5263, 2020 | 70 | 2020 |
| Regret bounds for transfer learning in Bayesian optimisation A Shilton, S Gupta, S Rana, S Venkatesh Artificial Intelligence and Statistics, 307-315, 2017 | 44 | 2017 |
| Distributed data fusion using support vector machines S Challa, M Palaniswami, A Shilton Proceedings of the Fifth International Conference on Information Fusion …, 2002 | 40 | 2002 |
| A division algebraic framework for multidimensional support vector regression A Shilton, DTH Lai, M Palaniswami IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 …, 2009 | 39 | 2009 |
| DP1SVM: A dynamic planar one-class support vector machine for Internet of Things environment A Shilton, S Rajasegarar, C Leckie, M Palaniswami 2015 International Conference on Recent Advances in Internet of Things (RIoT …, 2015 | 37 | 2015 |
| Iterative fuzzy support vector machine classification A Shilton, DTH Lai 2007 IEEE International Fuzzy Systems Conference, 1-6, 2007 | 36 | 2007 |
| Combined multiclass classification and anomaly detection for large-scale wireless sensor networks A Shilton, S Rajasegarar, M Palaniswami 2013 IEEE eighth international conference on intelligent sensors, sensor …, 2013 | 34 | 2013 |
| Fast supersymmetry phenomenology at the Large Hadron Collider using machine learning techniques A Buckley, A Shilton, MJ White Computer Physics Communications 183 (4), 960-970, 2012 | 32 | 2012 |
| Machine learning using support vector machines M Palaniswami, A Shilton, D Ralph, BD Owen International conference on Artificial Intelligence in Science and …, 2000 | 30 | 2000 |
| Adaptive support vector machines for regression M Palaniswami, A Shilton Proceedings of the 9th International Conference on Neural Information …, 2002 | 26 | 2002 |
| Exploiting strategy-space diversity for batch Bayesian optimization S Gupta, A Shilton, S Rana, S Venkatesh International conference on artificial intelligence and statistics, 538-547, 2018 | 24 | 2018 |
| Expected hypervolume improvement with constraints M Abdolshah, A Shilton, S Rana, S Gupta, S Venkatesh 2018 24th International Conference on Pattern Recognition (ICPR), 3238-3243, 2018 | 23 | 2018 |
| Human-AI collaborative Bayesian optimisation AK AV, S Rana, A Shilton, S Venkatesh Advances in Neural Information Processing Systems 35, 16233-16245, 2022 | 20 | 2022 |
| Regression models for estimating gait parameters using inertial sensors BK Santhiranayagam, D Lai, A Shilton, R Begg, M Palaniswami 2011 Seventh International Conference on Intelligent Sensors, Sensor …, 2011 | 20 | 2011 |
| Fairness improvement for black-box classifiers with Gaussian process D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh Information Sciences 576, 542-556, 2021 | 19 | 2021 |
