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cs.LG2025
Theoretical Foundations of Representation Learning using Unlabeled Data: Statistics and Optimization
Pascal Esser, Maximilian Fleissner, Debarghya Ghoshdastidar
Representation learning from unlabeled data has been extensively studied in statistics, data science and signal processing with a rich literature on techniques for dimension reduct…
cs.LG2025
A Probabilistic Model for Non-Contrastive Learning
Maximilian Fleissner, Pascal Esser, Debarghya Ghoshdastidar
Self-supervised learning (SSL) aims to find meaningful representations from unlabeled data by encoding semantic similarities through data augmentations. Despite its current popular…