NeurIPS 2020poster66 citations
Fair Hierarchical Clustering
Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii
Abstract
As machine learning has become more prevalent, researchers have begun to recognize the necessity of ensuring machine learning systems are fair. Recently, there has been an interest in defining a notion of fairness that mitigates over-representation in traditional clustering.
BibTeX
@inproceedings{NEURIPS2020_f10f2da9,
author = {Ahmadian, Sara and Epasto, Alessandro and Knittel, Marina and Kumar, Ravi and Mahdian, Mohammad and Moseley, Benjamin and Pham, Philip and Vassilvitskii, Sergei and Wang, Yuyan},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
pages = {21050--21060},
publisher = {Curran Associates, Inc.},
title = {Fair Hierarchical Clustering},
url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/f10f2da9a238b746d2bac55759915f0d-Paper.pdf},
volume = {33},
year = {2020}
}