4 citations · 4 across the 1 of their papers we have counts for
4 papers
Adaptive transfer learning
Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth
In transfer learning, we wish to make inference about a target population when we have access to data both from the distribution itself, and from a different but related source dis…
Random projections: data perturbation for classification problems
Timothy I. Cannings
Random projections offer an appealing and flexible approach to a wide range of large-scale statistical problems. They are particularly useful in high-dimensional settings, where we…
The correlation-assisted missing data estimator
Timothy I. Cannings, Yingying Fan
We introduce a novel approach to estimation problems in settings with missing data. Our proposal -- the Correlation-Assisted Missing data (CAM) estimator -- works by exploiting the…
A Framework for Implementing Machine Learning on Omics Data
Geoffroy Dubourg-Felonneau, Timothy Cannings, Fergal Cotter +4
The potential benefits of applying machine learning methods to -omics data are becoming increasingly apparent, especially in clinical settings. However, the unique characteristics…