7 citations · 24 across the 15 of their papers we have counts for
4 papers · 1 filter
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning
Alicia Curth, Alan Jeffares, Mihaela van der Schaar
Conventional statistical wisdom established a well-understood relationship between model complexity and prediction error, typically presented as a U-shaped curve reflecting a trans…
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization
Alan Jeffares, Tennison Liu, Jonathan Crabbé +2
Despite their success with unstructured data, deep neural networks are not yet a panacea for structured tabular data. In the tabular domain, their efficiency crucially relies on va…
Improving Adaptive Conformal Prediction Using Self-Supervised Learning
Nabeel Seedat, Alan Jeffares, Fergus Imrie +1
Conformal prediction is a powerful distribution-free tool for uncertainty quantification, establishing valid prediction intervals with finite-sample guarantees. To produce valid in…
Joint Training of Deep Ensembles Fails Due to Learner Collusion
Alan Jeffares, Tennison Liu, Jonathan Crabbé +1
Ensembles of machine learning models have been well established as a powerful method of improving performance over a single model. Traditionally, ensembling algorithms train their…