arXiv Machine Learning June 2, 2026 By Maedeh Zarvandi, Michael Timothy, Theresa Wasserer, Debarghya Ghoshdastidar

Interpretable Self-Supervised Learning via Representer Landmarks and Nystr\"om Approximation

Read the original on arXiv Machine Learning →

arXiv:2509. 24467v3 Announce Type: replace Abstract: Self-supervised learning (SSL) learns representations from massive unlabeled data, yet the resulting models typically operate as black boxes, necessitating domain-specific explanations.

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