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cs.LG2024
You Don't Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learning
Théo Moutakanni, Maxime Oquab, Marc Szafraniec +2
Self-Supervised learning (SSL) with Joint-Embedding Architectures (JEA) has led to outstanding performances. All instantiations of this paradigm were trained using strong and well-…
cs.LG2024
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Huy V. Vo, Vasil Khalidov, Timothée Darcet +10
Self-supervised features are the cornerstone of modern machine learning systems. They are typically pre-trained on data collections whose construction and curation typically requir…