| Bridging e-Health and the Internet of Things: The SPHERE Project N Zhu, T Diethe, M Camplani, L Tao, A Burrows, N Twomey, D Kaleshi, ... IEEE Intelligent Systems 30 (4), 39-46, 2015 | 324 | 2015 |
| A Comprehensive Study of Activity Recognition Using Accelerometers N Twomey, T Diethe, X Fafoutis, A Elsts, R McConville, P Flach, ... Informatics 5 (27), 2018 | 155 | 2018 |
| Distribution Calibration for Regression H Song, T Diethe, M Kull, P Flach 36th International Conference on Machine Learning (ICML), 2019 | 122 | 2019 |
| Multiview Fisher discriminant analysis T Diethe, DR Hardoon, J Shawe-Taylor NIPS workshop on learning from multiple sources, 2008 | 119 | 2008 |
| Privacy-and utility-preserving textual analysis via calibrated multivariate perturbations O Feyisetan, B Balle, T Drake, T Diethe Proceedings of the 13th international conference on web search and data …, 2020 | 118 | 2020 |
| Optimal Continual Learning has Perfect Memory and is NP-hard J Knoblauch, H Husain, T Diethe 37th International Conference on Machine Learning (ICML), 2020 | 113 | 2020 |
| SPHERE: A sensor platform for healthcare in a residential environment P Woznowski, A Burrows, T Diethe, X Fafoutis, J Hall, S Hannuna, ... Designing, Developing, and Facilitating Smart Cities: Urban Design to IoT …, 2017 | 90 | 2017 |
| The SPHERE challenge: Activity recognition with multimodal sensor data N Twomey, T Diethe, M Kull, H Song, M Camplani, S Hannuna, X Fafoutis, ... arXiv preprint arXiv:1603.00797, 2016 | 89 | 2016 |
| Continual Learning in Practice T Diethe, T Borchert, E Thereska, B de Balle Pigem, N Lawrence NeurIPS Workshop on Continual Learning, 2018 | 87 | 2018 |
| Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text O Feyisetan, T Diethe, T Drake IEEE International Conference on Data Mining, ICDM 2019, Beijing, December 8-11, 2019 | 79 | 2019 |
| Designing, developing, and facilitating smart cities: urban design to IoT solutions V Angelakis, E Tragos, HC Pöhls, A Kapovits, A Bassi Springer, 2016 | 65 | 2016 |
| Constructing nonlinear discriminants from multiple data views T Diethe, DR Hardoon, J Shawe-Taylor Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010 | 58 | 2010 |
| Active transfer learning for activity recognition T Diethe, N Twomey, P Flach European Symposium on Artificial Neural Networks, Computational Intelligence …, 2016 | 52 | 2016 |
| Unsupervised learning of sensor topologies for improving activity recognition in smart environments N Twomey, T Diethe, I Craddock, P Flach Neurocomputing 234, 93-106, 2017 | 47 | 2017 |
| Online learning with (multiple) kernels: A review T Diethe, M Girolami Neural computation 25 (3), 567-625, 2013 | 47 | 2013 |
| Automatic discovery of privacy-utility Pareto fronts B Avent, J Gonzalez, T Diethe, A Paleyes, B Balle Proceedings on Privacy Enhancing Technologies 2020 (4), 5--23, 2019 | 34 | 2019 |
| Compressed sampling for pulse Doppler radar GE Smith, T Diethe, Z Hussain, J Shawe-Taylor, DR Hardoon 2010 IEEE Radar Conference, 887-892, 2010 | 33 | 2010 |
| Model-Based Machine Learning J Winn, CM Bishop, T Diethe Microsoft Research, 2015 | 28* | 2015 |
| -IRT: A New Item Response Model and its Applications Y Chen, RBC Prudêncio, T Diethe, P Flach Proceedings of the 22nd International Conference on Artificial Intelligence …, 2019 | 26 | 2019 |
| Probabilistic sensor fusion for ambient assisted living T Diethe, N Twomey, M Kull, P Flach, I Craddock arXiv preprint arXiv:1702.01209, 2017 | 24 | 2017 |
Peter FlachProfessor of Artificial Intelligence, Department of Computer Science, University of BristolVerified email at bristol.ac.uk
