4min chapter

Machine Learning Street Talk (MLST) cover image

#86 - Prof. YANN LECUN and Dr. RANDALL BALESTRIERO - SSL, Data Augmentation, Reward isn't enough [NEURIPS2022]

Machine Learning Street Talk (MLST)

CHAPTER

The Representational Capacity of Self-Supervised Learning

I think ultimately, I think self-supervised methods that use multiple criteria are going to be the main method to train. The big question is can you build those surrogate tasks without requiring expensive manual labeling? And this is what the documentation does. It's just a way of generating labeled data if you want. Which is not really labels, but it's kind of similar without human intervention.

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