NeurIPS 2020poster14 citations
Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds
Nicholas Harvey, Christopher Liaw, Tasuku Soma
Abstract
We consider the problem of nonnegative submodular maximization in the online setting. At time step t, an algorithm selects a set S
BibTeX
@inproceedings{NEURIPS2020_0163cceb,
author = {Harvey, Nicholas and Liaw, Christopher and Soma, Tasuku},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
pages = {123--133},
publisher = {Curran Associates, Inc.},
title = {Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds},
url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/0163cceb20f5ca7b313419c068abd9dc-Paper.pdf},
volume = {33},
year = {2020}
}