@inbook{fe9a042520e749e9be1ae93027ff10a7,
title = "Achieving Long-Term Fairness in Submodular Maximization Through Randomization",
abstract = "Submodular function optimization is applied in ML and data analysis, including diverse dataset summarization. Fairness-aware algorithms are essential for handling sensitive attributes. Our research investigates the problem of maximizing a monotone submodular function while adhering to constraints on the expected number of selected items per group. Our goal is to compute a distribution over feasible sets, and to achieve this, we develop a series of approximation algorithms.",
author = "Shaojie Tang and Jing Yuan and Twumasi Mensah-Boateng",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.",
year = "2024",
doi = "10.1007/978-3-031-46826-1\_13",
language = "English",
series = "AIRO Springer Series",
publisher = "Springer Nature",
pages = "161--173",
booktitle = "AIRO Springer Series",
}