no code implementations • NeurIPS 2021 • Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi
The emerging field of learning-augmented online algorithms uses ML techniques to predict future input parameters and thereby improve the performance of online algorithms.
no code implementations • ICML 2020 • Keerti Anand, Rong Ge, Debmalya Panigrahi
A popular line of recent research incorporates ML advice in the design of online algorithms to improve their performance in typical instances.
no code implementations • 8 May 2022 • Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi
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.