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A Regression Approach to Learning-Augmented Online Algorithms
The emerging field of learning-augmented online algorithms uses ML techniques to predict future input parameters and thereby improve the performance of online algorithms.
Customizing ML Predictions for Online Algorithms
A popular line of recent research incorporates ML advice in the design of online algorithms to improve their performance in typical instances.
Online Algorithms with Multiple Predictions
In this paper, we give a generic algorithmic framework for online covering problems with multiple predictions that obtains an online solution that is competitive against the performance of the best predictor.
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