408 citations · 492 across the 14 of their papers we have counts for
3 papers · 1 filter
When does Active Learning Work?
Lewis Evans, Niall M. Adams, Christoforos Anagnostopoulos
Active Learning (AL) methods seek to improve classifier performance when labels are expensive or scarce. We consider two central questions: Where does AL work? How much does it hel…
Targeting Optimal Active Learning via Example Quality
Lewis P. G. Evans, Niall M. Adams, Christoforos Anagnostopoulos
In many classification problems unlabelled data is abundant and a subset can be chosen for labelling. This defines the context of active learning (AL), where methods systematically…
A general decision framework for structuring computation using Data Directional Scaling to process massive similarity matrices
Daniel John Lawson, Niall M Adams
As datasets grow it becomes infeasible to process them completely with a desired model. For giant datasets, we frame the order in which computation is performed as a decision probl…