Author

Samory Kpotufe

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#artificial intelligence Preprint Aug 2024

Help Me Help You: The Aggregate Value of Source and Target Data in Transfer Learning

This work identifies and characterize an interesting dichotomy in the rates achievable in the supervised setting: there is a weak transfer regime where optimal rates are determined by information in either the source or target dataset but not both, and a strong transfer regime where much faster target rates are achieva...

Steve Hanneke, Samory Kpotufe · 3 citations

#machine learning Preprint Sep 2026

An Analysis of Self-supervised Pre-training with Dependent Samples

It is shown that pooling augmentations together, despite inter-dependencies, is a better alternative than the baseline of partitioning the data into subsets of independent data and provides an intuition behind the practical preference towards using many augmentations.

Maximilian Fleissner, D. Ghoshdastidar, Samory Kpotufe · 0 citations