| FACE: feasible and actionable counterfactual explanations R Poyiadzi, K Sokol, R Santos-Rodriguez, T De Bie, P Flach Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 344-350, 2020 | 380 | 2020 |
| FAT Forensics: A Python toolbox for implementing and deploying fairness, accountability and transparency algorithms in predictive systems K Sokol, A Hepburn, R Poyiadzi, M Clifford, R Santos-Rodriguez, P Flach arXiv preprint arXiv:2209.03805, 2022 | 26 | 2022 |
| Label propagation for learning with label proportions R Poyiadzi, R Santos-Rodriguez, N Twomey 2018 IEEE 28th International Workshop on Machine Learning for Signal …, 2018 | 12 | 2018 |
| The weak supervision landscape R Poyiadzi, D Bacaicoa-Barber, J Cid-Sueiro, M Perello-Nieto, P Flach, ... 2022 IEEE International Conference on Pervasive Computing and Communications …, 2022 | 10 | 2022 |
| On the overlooked issue of defining explanation objectives for local-surrogate explainers R Poyiadzi, X Renard, T Laugel, R Santos-Rodriguez, M Detyniecki arXiv preprint arXiv:2106.05810, 2021 | 10 | 2021 |
| Detecting signatures of early-stage dementia with behavioural models derived from sensor data R Poyiadzi, W Yang, Y Ben-Shlomo, I Craddock, L Coulthard, ... arXiv preprint arXiv:2007.03615, 2020 | 10 | 2020 |
| Tijl De Bie, and Peter Flach R Poyiadzi, K Sokol, R Santos-Rodriguez FACE: Feasible and actionable counterfactual explanations, 2019 | 10 | 2019 |
| Uncertainty quantification of surrogate explanations: an ordinal consensus approach J Schulz, R Poyiadzi, R Santos-Rodriguez arXiv preprint arXiv:2111.09121, 2021 | 8 | 2021 |
| Active learning with label proportions R Poyiadzis, R Santos-Rodriguez, N Twomey ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 7 | 2019 |
| Understanding surrogate explanations: the interplay between complexity, fidelity and coverage R Poyiadzi, X Renard, T Laugel, R Santos-Rodriguez, M Detyniecki arXiv preprint arXiv:2107.04309, 2021 | 6 | 2021 |
| Domain generalisation for apparent emotional facial expression recognition across age-groups R Poyiadzi, J Shen, S Petridis, Y Wang, M Pantic arXiv preprint arXiv:2110.09168, 2021 | 5 | 2021 |
| Statistical hypothesis testing for class-conditional label noise R Poyiadzi, W Yang, N Twomey, R Santos-Rodriguez European Conference on Machine Learning and Principles and Practice of …, 2022 | 3 | 2022 |
| Ordinal label proportions R Poyiadzi, R Santos-Rodriguez, T De Bie Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 3 | 2019 |
| Detecting and monitoring behavioural patterns in individuals with cognitive disorders in the home environment with partial annotations W Yang, R Poyiadzi, Y Ben-Shlomo, I Craddock, L Coulthard, ... Integrating Artificial Intelligence and IoT for Advanced Health Informatics …, 2022 | 2 | 2022 |
| Feasible and actionable counterfactual explanations R Poyiadzi, K Sokol, R Santos-Rodriguez, T De Bie, P Flach New York: Association for Computing Machinery, 2020 | 2 | 2020 |
| Ordinal regression as structured classification N Twomey, R Poyiadzi, C Mann, R Santos-Rodríguez arXiv preprint arXiv:1905.13658, 2019 | 2 | 2019 |
| Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood W Yang, R Poyiadzi, N Twomey, R Santos-Rodriguez Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21744 …, 2024 | | 2024 |
| The Use of Home-Based Behaviours for Detecting Early Dementia: Protocol for the CUBOId Study J Selwood, N Twomey, I Craddock, E Coulthard, DP Kumpik, M Newson, ... medRxiv, 2024.02. 21.24303130, 2024 | | 2024 |
| Hypothesis Testing for Class-Conditional Label Noise R Poyiadzi, W Yang, N Twomey, R Santos-Rodriguez Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | | 2022 |
| Equitable Ability Estimation in Neurodivergent Student Populations with Zero-Inflated Learner Models N Twomey, S McMullan, A Elhalal, R Poyiadzi, L Vaquero arXiv preprint arXiv:2203.10170, 2022 | | 2022 |
