682 citations · 1.3k across the 13 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2025
DataRater: Meta-Learned Dataset Curation
Dan A. Calian, Gregory Farquhar, Iurii Kemaev +9
The quality of foundation models depends heavily on their training data. Consequently, great efforts have been put into dataset curation. Yet most approaches rely on manual tuning…
stat.ML2020
A Self-Tuning Actor-Critic Algorithm
Tom Zahavy, Zhongwen Xu, Vivek Veeriah +5
Reinforcement learning algorithms are highly sensitive to the choice of hyperparameters, typically requiring significant manual effort to identify hyperparameters that perform well…
stat.ML2013★ 19 cited
Estimating the Maximum Expected Value: An Analysis of (Nested) Cross Validation and the Maximum Sample Average
Hado van Hasselt
We investigate the accuracy of the two most common estimators for the maximum expected value of a general set of random variables: a generalization of the maximum sample average, a…