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Exploring Open-Ended Algorithms: POET

Machine Learning Street Talk (MLST)

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Navigating Algorithm Optimization

This chapter explores the intricacies of algorithm optimization, focusing on the POET framework and its ties to self-supervised learning. It delves into the balance between exploratory capabilities and desired outcomes, discussing potential solutions for enhancing performance in tasks like image classification.

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