15 citations · 53 across the 16 of their papers we have counts for
17 papers
Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood
Weisong Yang, Rafael Poyiadzi, Niall Twomey +1
In supervised learning, automatically assessing the quality of the labels before any learning takes place remains an open research question. In certain particular cases, hypothesis…
Low-count Time Series Anomaly Detection
Philipp Renz, Kurt Cutajar, Niall Twomey +2
Low-count time series describe sparse or intermittent events, which are prevalent in large-scale online platforms that capture and monitor diverse data types. Several distinct chal…
Equitable Ability Estimation in Neurodivergent Student Populations with Zero-Inflated Learner Models
Niall Twomey, Sarah McMullan, Anat Elhalal +2
At present, the educational data mining community lacks many tools needed for ensuring equitable ability estimation for Neurodivergent (ND) learners. On one hand, most learner mode…
Towards Continuous Compounding Effects and Agile Practices in Educational Experimentation
Luis M. Vaquero, Niall Twomey, Miguel Patricio Dias +2
Randomised control trials are currently the definitive gold standard approach for formal educational experiments. Although conclusions from these experiments are highly credible, t…
Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora
Mikhail Fain, Niall Twomey, Danushka Bollegala
Cross-lingual text representations have gained popularity lately and act as the backbone of many tasks such as unsupervised machine translation and cross-lingual information retrie…
Evaluation of Field-Aware Neural Ranking Models for Recipe Search
Kentaro Takiguchi, Mikhail Fain, Niall Twomey +1
Explicitly modelling field interactions and correlations in complex document structures has recently gained popularity in neural document embedding and retrieval tasks. Although th…
Hypothesis Testing for Class-Conditional Label Noise
Rafael Poyiadzi, Weisong Yang, Niall Twomey +1
In this paper we provide machine learning practitioners with tools to answer the question: is there class-conditional noise in my labels? In particular, we present hypothesis tests…
Non-Linear Multiple Field Interactions Neural Document Ranking
Kentaro Takiguchi, Niall Twomey, Luis M. Vaquero
Ranking tasks are usually based on the text of the main body of the page and the actions (clicks) of users on the page. There are other elements that could be leveraged to better c…
Towards Multi-Language Recipe Personalisation and Recommendation
Niall Twomey, Mikhail Fain, Andrey Ponikar +1
Multi-language recipe personalisation and recommendation is an under-explored field of information retrieval in academic and production systems. The existing gaps in our current un…
Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data
Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo +5
There is a pressing need to automatically understand the state and progression of chronic neurological diseases such as dementia. The emergence of state-of-the-art sensing platform…
Dividing and Conquering Cross-Modal Recipe Retrieval: from Nearest Neighbours Baselines to SoTA
Mikhail Fain, Niall Twomey, Andrey Ponikar +2
We propose a novel non-parametric method for cross-modal recipe retrieval which is applied on top of precomputed image and text embeddings. By combining our method with standard ap…
HyperStream: a Workflow Engine for Streaming Data
Tom Diethe, Meelis Kull, Niall Twomey +5
This paper describes HyperStream, a large-scale, flexible and robust software package, written in the Python language, for processing streaming data with workflow creation capabili…
Ordinal Regression as Structured Classification
Niall Twomey, Rafael Poyiadzi, Callum Mann +1
This paper extends the class of ordinal regression models with a structured interpretation of the problem by applying a novel treatment of encoded labels. The net effect of this is…
Neural ODEs with stochastic vector field mixtures
Niall Twomey, Michał Kozłowski, Raúl Santos-Rodríguez
It was recently shown that neural ordinary differential equation models cannot solve fundamental and seemingly straightforward tasks even with high-capacity vector field representa…
Label Propagation for Learning with Label Proportions
Rafael Poyiadzi, Raul Santos-Rodriguez, Niall Twomey
Learning with Label Proportions (LLP) is the problem of recovering the underlying true labels given a dataset when the data is presented in the form of bags. This paradigm is parti…
Probabilistic Sensor Fusion for Ambient Assisted Living
Tom Diethe, Niall Twomey, Meelis Kull +2
There is a widely-accepted need to revise current forms of health-care provision, with particular interest in sensing systems in the home. Given a multiple-modality sensor platform…
The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data
Niall Twomey, Tom Diethe, Meelis Kull +8
This paper outlines the Sensor Platform for HEalthcare in Residential Environment (SPHERE) project and details the SPHERE challenge that will take place in conjunction with Europea…