2 papers
cs.LG2026
Crossing the Validation Crisis: Cross-Validation Reduces Benchmarking Variance Surprisingly Well
Célestin Eve, Gaël Varoquaux, Thomas Moreau
Modern machine learning progresses through empirical work, benchmarking new methods to evaluate relative performance. However, the statistical variability inherent to evaluation -…
cs.LG2025
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities
Yanis Lalou, Théo Gnassounou, Antoine Collas +6
Unsupervised Domain Adaptation (DA) consists of adapting a model trained on a labeled source domain to perform well on an unlabeled target domain with some data distribution shift.…