Learning-augmented algorithms are a class of algorithms that combine traditional computational methods with machine learning techniques to enhance their performance and efficiency. The idea is to leverage the strengths of both approaches—drawing on the rigor and reliability of established algorithms while incorporating the adaptability and predictive power of machine learning.

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