45 citations · 112 across the 11 of their papers we have counts for
5 papers · 1 filter
Mitigating sampling bias in risk-based active learning via an EM algorithm
Aidan J. Hughes, Lawrence A. Bull, Paul Gardner +2
Risk-based active learning is an approach to developing statistical classifiers for online decision-support. In this approach, data-label querying is guided according to the expect…
Improving decision-making via risk-based active learning: Probabilistic discriminative classifiers
Aidan J. Hughes, Paul Gardner, Lawrence A. Bull +2
Gaining the ability to make informed decisions on operation and maintenance of structures provides motivation for the implementation of structural health monitoring (SHM) systems.…
On statistic alignment for domain adaptation in structural health monitoring
Jack Poole, Paul Gardner, Nikolaos Dervilis +2
The practical application of structural health monitoring (SHM) is often limited by the availability of labelled data. Transfer learning - specifically in the form of domain adapta…
On partitioning of an SHM problem and parallels with transfer learning
G. Tsialiamanis, D. J. Wagg, P. A. Gardner +2
In the current work, a problem-splitting approach and a scheme motivated by transfer learning is applied to a structural health monitoring problem. The specific problem in this cas…
On robust risk-based active-learning algorithms for enhanced decision support
Aidan J. Hughes, Lawrence A. Bull, Paul Gardner +2
Classification models are a fundamental component of physical-asset management technologies such as structural health monitoring (SHM) systems and digital twins. Previous work intr…