4 papers · 1 filter
Active Learning and Transfer Learning for Anomaly Detection in Time-Series Data
John D. Kelleher, Matthew Nicholson, Rahul Agrahari +1
This paper examines the effectiveness of combining active learning and transfer learning for anomaly detection in cross-domain time-series data. Our results indicate that there is…
Extending TWIG: Zero-Shot Predictive Hyperparameter Selection for KGEs based on Graph Structure
Jeffrey Sardina, John D. Kelleher, Declan O'Sullivan
Knowledge Graphs (KGs) have seen increasing use across various domains -- from biomedicine and linguistics to general knowledge modelling. In order to facilitate the analysis of kn…
A Survey on Knowledge Graph Structure and Knowledge Graph Embeddings
Jeffrey Sardina, John D. Kelleher, Declan O'Sullivan
Knowledge Graphs (KGs) and their machine learning counterpart, Knowledge Graph Embedding Models (KGEMs), have seen ever-increasing use in a wide variety of academic and applied set…
A framework for measuring the training efficiency of a neural architecture
Eduardo Cueto-Mendoza, John D. Kelleher
Measuring Efficiency in neural network system development is an open research problem. This paper presents an experimental framework to measure the training efficiency of a neural…