@inproceedings{5c2b0e2fb9c548c3ba196afbbd2c9334,
title = "Finding Bipartite Components in Hypergraphs",
abstract = "Hypergraphs are important objects to model ternary or higher-order relations of objects, and have a number of applications in analysing many complex datasets occurring in practice. In this work we study a new heat diffusion process in hypergraphs, and employ this process to design a polynomial-time algorithm that approximately finds bipartite components in a hypergraph. We theoretically prove the performance of our proposed algorithm, and compare it against the previous state-of-the-art through extensive experimental analysis on both synthetic and real-world datasets. We find that our new algorithm consistently and significantly outperforms the previous state-of-the-art across a wide range of hypergraphs.",
author = "Peter Macgregor and He Sun",
year = "2021",
month = dec,
day = "14",
language = "English",
volume = "34",
series = "Advances in Neural Information Processing Systems",
publisher = "Curran Associates Inc",
pages = "7912--7923",
editor = "M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and Vaughan, {J. Wortman}",
booktitle = "Advances in Neural Information Processing Systems 2022",
note = "35th Conference on Neural Information Processing Systems, NeurIPS 2021 ; Conference date: 06-12-2021 Through 14-12-2021",
}