33 citations · 142 across the 20 of their papers we have counts for
5 papers · 1 filter
Density Ratio Estimation and Neyman Pearson Classification with Missing Data
Josh Givens, Song Liu, Henry W J Reeve
Density Ratio Estimation (DRE) is an important machine learning technique with many downstream applications. We consider the challenge of DRE with missing not at random (MNAR) data…
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…
Optimistic bounds for multi-output prediction
Henry WJ Reeve, Ata Kaban
We investigate the challenge of multi-output learning, where the goal is to learn a vector-valued function based on a supervised data set. This includes a range of important proble…
Classification with unknown class-conditional label noise on non-compact feature spaces
Henry W J Reeve, Ata Kaban
We investigate the problem of classification in the presence of unknown class-conditional label noise in which the labels observed by the learner have been corrupted with some unkn…
To Ensemble or Not Ensemble: When does End-To-End Training Fail?
Andrew M. Webb, Charles Reynolds, Wenlin Chen +4
End-to-End training (E2E) is becoming more and more popular to train complex Deep Network architectures. An interesting question is whether this trend will continue-are there any c…