Dr Niall Twomey

Latest publications

• Poyiadzi, R, Santos-Rodriguez, R & Twomey, N, 2019, ‘Active Learning with Label Proportions’. in: 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers (IEEE), pp. 3097-3101
• Twomey, N, Chen, H, Diethe, T & Flach, P, 2019, ‘An Application of Hierarchical Gaussian Processes to the Detection of Anomalies in Star Light Curves’. Neurocomputing, vol 342., pp. 152-163
• Chen, H, Diethe, T, Twomey, N & Flach, P, 2018, ‘Anomaly Detection in Star Light Curves using Hierarchical Gaussian Processes’. in: European Symposium on Artificial Neural Networks: ESANN. European Symposium on Artificial Neural Networks, Bruges
• Poyiadzi, R, Santos-Rodriguez, R & Twomey, N, 2018, ‘Label Propagation for Learning with Label Proportions’. in: 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP 2018): Proceedings of a meeting held 17-20 September 2018, Aalborg, Denmark. Institute of Electrical and Electronics Engineers (IEEE), pp. 264-270
• Tonkin, EL, Burrows, A, Woznowski, PR, Laskowski, P, Yordanova, K, Twomey, N & Craddock, I, 2018, ‘Talk, text, tag? Understanding self-annotation of smart home data from a user’s perspective’. Sensors, vol 18.
• Santos-Rodriguez, R & Twomey, N, 2018, ‘Efficient approximate representations of computationally expensive features’. in: ESANN 2018 proceedings: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning., Bruges
• Elsts, A, Burghardt, T, Byrne, D, Camplani, M, Damen, D, Fafoutis, X, Hannuna, S, Harwin, W, Holmes, M, Janko, B, Lopez, VP, Masullo, A, Mirmehdi, M, Oikonomou, G, Piechocki, R, Sherratt, S, Tonkin, EL, Twomey, N, Vafeas, A, Woznowski, PR & Craddock, I, 2018, ‘A Guide to the SPHERE 100 Homes Study Dataset’.
• McConville, R, Santos-Rodriguez, R & Twomey, N, 2018, ‘Person Identification and Discovery With Wrist Worn Accelerometer Data’. in: Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2018., pp. 615-620
• Elsts, A, McConville, R, Fafoutis, X, Twomey, N, Piechocki, R, Santos-Rodriguez, R & Craddock, I, 2018, ‘On-Board Feature Extraction from Acceleration Data for Activity Recognition’. in: EWSN ’18: Proceedings of the 2018 International Conference on Embedded Wireless Systems and Networks. Association for Computing Machinery (ACM), pp. 163-186
• Diethe, T, Nieto, MP, Tonkin, E, Holmes, M, Sokol, K, Twomey, N, Kull, M, Song, H & Flach, P, 2018, ‘Releasing eHealth analytics into the wild: Lessons learnt from the SPHERE project’. in: KDD'18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery (ACM), pp. 243-252