Niall Twomey

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 42

Top Topics

Gaussian Process

Accelerometer Data

Hypothesis Testing

Activity Recognition

Top Venues

Publications

Joseph Early, Gavin K. C. Cheung, Kurt Cutajar, Hanting Xie, Jas Kandola, Niall Twomey
Inherently Interpretable Time Series Classification via Multiple Instance Learning. ICLR (2024)
Weisong Yang, Rafael Poyiadzi, Niall Twomey, Raúl Santos-Rodríguez
Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood. AAAI (2024)
Weisong Yang, Rafael Poyiadzi, Niall Twomey, Raúl Santos-Rodríguez
Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood. CoRR (2023)
Philipp Renz, Kurt Cutajar, Niall Twomey, Gavin K. C. Cheung, Hanting Xie
Low-count Time Series Anomaly Detection. CoRR (2023)
Joseph Early, Gavin K. C. Cheung, Kurt Cutajar, Hanting Xie, Jas Kandola, Niall Twomey
Inherently Interpretable Time Series Classification via Multiple Instance Learning. CoRR (2023)
Philipp Renz, Kurt Cutajar, Niall Twomey, Gavin K. C. Cheung, Hanting Xie
Low-Count Time Series Anomaly Detection. MLSP (2023)
Niall Twomey, Sarah McMullan, Anat Elhalal, Rafael Poyiadzi, Luis Miguel Vaquero
Equitable Ability Estimation in Neurodivergent Student Populations with Zero-Inflated Learner Models. CoRR (2022)
Niall Twomey, Sarah McMullan, Anat Elhalal, Rafael Poyiadzi, Luis M. Vaquero
Equitable Ability Estimation in Neurodivergent Student Populations with Zero-Inflated Learner Models. EDM (2022)
Rafael Poyiadzi, Weisong Yang, Niall Twomey, Raúl Santos-Rodríguez
Hypothesis Testing for Class-Conditional Label Noise. ECML/PKDD (3) (2022)
Rafael Poyiadzi, Weisong Yang, Niall Twomey, Raúl Santos-Rodríguez
Statistical Hypothesis Testing for Class-Conditional Label Noise. CoRR (2021)
Kentaro Takiguchi, Niall Twomey, Luis M. Vaquero
Multi-Field Models in Neural Recipe Ranking - An Early Exploratory Study. CoRR (2021)
Luis M. Vaquero, Niall Twomey, Miguel Patricio Dias, Massimo Camplani, Robert Hardman
Towards Continuous Compounding Effects and Agile Practices in Educational Experimentation. CoRR (2021)
Mikhail Fain, Niall Twomey, Danushka Bollegala
Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora. CoRR (2021)
Mikhail Fain, Niall Twomey, Danushka Bollegala
Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora. SIGIR (2021)
Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey
Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data. AAI4H@ECAI (2020)
Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey
Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data. CoRR (2020)
Atis Elsts, Niall Twomey, Ryan McConville, Ian Craddock
Energy-efficient activity recognition framework using wearable accelerometers. J. Netw. Comput. Appl. 168 (2020)
Kentaro Takiguchi, Niall Twomey, Luis M. Vaquero
Non-Linear Multiple Field Interactions Neural Document Ranking. CoRR (2020)
Mikhail Fain, Andrey Ponikar, Nadine Sarraf, Niall Twomey
Towards Multi-Language Recipe Personalisation and Recommendation. CoRR (2020)
Niall Twomey, Michal Kozlowski, Raúl Santos-Rodríguez
Neural ODEs with Stochastic Vector Field Mixtures. ECAI (2020)
Niall Twomey, Mikhail Fain, Andrey Ponikar, Nadine Sarraf
Towards Multi-Language Recipe Personalisation and Recommendation. RecSys (2020)
Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey
Active Learning with Label Proportions. ICASSP (2019)
Niall Twomey, Haoyan Chen, Tom Diethe, Peter A. Flach
An application of hierarchical Gaussian processes to the detection of anomalies in star light curves. Neurocomputing 342 (2019)
Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perelló-Nieto, Emma Tonkin, Peter A. Flach
HyperStream: a Workflow Engine for Streaming Data. CoRR (2019)
Niall Twomey, Rafael Poyiadzi, Callum Mann, Raúl Santos-Rodríguez
Ordinal Regression as Structured Classification. CoRR (2019)
Niall Twomey, Michal Kozlowski, Raúl Santos-Rodríguez
Neural ODEs with stochastic vector field mixtures. CoRR (2019)
Ryan McConville, Raúl Santos-Rodríguez, Niall Twomey
Person Identification and Discovery With Wrist Worn Accelerometer Data. ESANN (2018)
Haoyan Chen, Tom Diethe, Niall Twomey, Peter A. Flach
Anomaly detection in star light curves using hierarchical Gaussian processes. ESANN (2018)
Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey
Label Propagation for Learning with Label Proportions. CoRR (2018)
Tom Diethe, Mike Holmes, Meelis Kull, Miquel Perelló-Nieto, Kacper Sokol, Hao Song, Emma Tonkin, Niall Twomey, Peter A. Flach
Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project. KDD (2018)
Emma Tonkin, Alison Burrows, Przemyslaw Woznowski, Pawel Laskowski, Kristina Y. Yordanova, Niall Twomey, Ian Craddock
Talk, Text, Tag? Understanding Self-Annotation of Smart Home Data from a User's Perspective. Sensors 18 (7) (2018)
Atis Elsts, Ryan McConville, Xenofon Fafoutis, Niall Twomey, Robert J. Piechocki, Raúl Santos-Rodriguez, Ian Craddock
On-Board Feature Extraction from Acceleration Data for Activity Recognition. EWSN (2018)
Raúl Santos-Rodríguez, Niall Twomey
Efficient approximate representations for computationally expensive features. ESANN (2018)
Niall Twomey, Tom Diethe, Xenofon Fafoutis, Atis Elsts, Ryan McConville, Peter A. Flach, Ian Craddock
A Comprehensive Study of Activity Recognition Using Accelerometers. Informatics 5 (2) (2018)
Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey
Label Propagation for Learning with Label proportions. MLSP (2018)
Niall Twomey, Tom Diethe, Ian Craddock, Peter A. Flach
Unsupervised learning of sensor topologies for improving activity recognition in smart environments. Neurocomputing 234 (2017)
Tom Diethe, Niall Twomey, Meelis Kull, Peter A. Flach, Ian Craddock
Probabilistic Sensor Fusion for Ambient Assisted Living. CoRR (2017)
Przemyslaw Woznowski, Emma Tonkin, Pawel Laskowski, Niall Twomey, Kristina Y. Yordanova, Alison Burrows
Talk, text or tag? PerCom Workshops (2017)
Niall Twomey, Tom Diethe, Meelis Kull, Hao Song, Massimo Camplani, Sion L. Hannuna, Xenofon Fafoutis, Ni Zhu, Pete Woznowski, Peter A. Flach, Ian Craddock
The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data. CoRR (2016)
Tom Diethe, Niall Twomey, Peter A. Flach
BDL.NET: Bayesian dictionary learning in Infer.NET. MLSP (2016)
Niall Twomey, Tom Diethe, Peter A. Flach
On the need for structure modelling in sequence prediction. Mach. Learn. 104 (2-3) (2016)
Tom Diethe, Niall Twomey, Peter A. Flach
Active transfer learning for activity recognition. ESANN (2016)
Ni Zhu, Tom Diethe, Massimo Camplani, Lili Tao, Alison Burrows, Niall Twomey, Dritan Kaleshi, Majid Mirmehdi, Peter A. Flach, Ian Craddock
Bridging e-Health and the Internet of Things: The SPHERE Project. IEEE Intell. Syst. 30 (4) (2015)
Xenofon Fafoutis, Evangelos Mellios, Niall Twomey, Tom Diethe, Geoffrey S. Hilton, Robert J. Piechocki
An RSSI-based wall prediction model for residential floor map construction. WF-IoT (2015)
Tom Diethe, Niall Twomey, Peter A. Flach
Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics. ECML/PKDD (2) (2015)
Niall Twomey, Andrey Temko, Jonathan O'B. Hourihane, William P. Marnane
Automated Detection of Perturbed Cardiac Physiology During Oral Food Allergen Challenge in Children. IEEE J. Biomed. Health Informatics 18 (3) (2014)
Niall Twomey, Peter A. Flach
A Machine Learning Approach to Objective Cardiac Event Detection. CISIS (2014)
Niall Twomey, Andrey Temko, Jonathan O'B. Hourihane, William P. Marnane
Allergy detection with statistical modelling of HRV-based non-reaction baseline features. ISABEL (2011)
Niall Twomey, Stephen Faul, William P. Marnane
Comparison of accelerometer-based energy expenditure estimation algorithms. PervasiveHealth (2010)