4 citations · 4 across the 2 of their papers we have counts for
3 papers · 1 filter
How many classifiers do we need?
Hyunsuk Kim, Liam Hodgkinson, Ryan Theisen +1
As performance gains through scaling data and/or model size experience diminishing returns, it is becoming increasingly popular to turn to ensembling, where the predictions of mult…
A PAC-Bayesian Perspective on the Interpolating Information Criterion
Liam Hodgkinson, Chris van der Heide, Robert Salomone +2
Deep learning is renowned for its theory-practice gap, whereby principled theory typically fails to provide much beneficial guidance for implementation in practice. This has been h…
When are ensembles really effective?
Ryan Theisen, Hyunsuk Kim, Yaoqing Yang +2
Ensembling has a long history in statistical data analysis, with many impactful applications. However, in many modern machine learning settings, the benefits of ensembling are less…