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#92 - SARA HOOKER - Fairness, Interpretability, Language Models

Machine Learning Street Talk (MLST)

CHAPTER

Exploring the Nuances of Self-Supervised Learning and Robustness

This chapter delves into self-supervised learning, contrasting it with fully supervised learning and evaluating the role of labels in training. It also investigates the memorization capabilities of self-supervised models and their implications for learning rare instances while questioning current robustness measures in the field.

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