4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Online Quantile Omniprediction for Proper Losses
Hyunsuk Kim, Isaac Gibbs, Michael W. Mahoney +1
The task of constructing a predictor that is simultaneously accurate under multiple evaluation metrics has been popularized recently under the name omniprediction. Prior work in th…
stat.ML2024
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…
stat.ML2023★ 4 cited
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…