@inproceedings{52760ebc8c8b4e5fb779d9e8a75ca232,
title = "Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs",
abstract = "The landing probability of a vertex in a hypergraph is the probability of a random walk ending at the vertex after making a prescribed number of steps. Landing probabilities are of importance for a number of learning tasks on hypergraphs, including higher-order PageRanks and (local) community detection. We perform the first mean-field study of landing probabilities of random walks on hypergraphs and examine clique-expansion and tensor-based methods. In particular, we evaluate the mean-field characteristics of the two methods over a class of random hypergraph models for the task of seed-set community expansion. We determine parameter regimes in which one method outperforms the other and propose a new hybrid expansion method termed 'partial clique-expansion' to reduce the projection distortion and reduce the complexity of tensor-based methods on partially expanded hypergraphs.",
author = "Eli Chien and Pan Li and Olgica Milenkovic",
note = "Acknowledgment: The work was supported by the NSF grant 1956384 and the NSF Center for Science of Information (CSoI) housed at Purdue University.; 2021 IEEE Information Theory Workshop, ITW 2021 ; Conference date: 17-10-2021 Through 21-10-2021",
year = "2021",
doi = "10.1109/ITW48936.2021.9611457",
language = "English (US)",
series = "2021 IEEE Information Theory Workshop, ITW 2021 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE Information Theory Workshop, ITW 2021 - Proceedings",
address = "United States",
}