@inproceedings{fbf33c805a39411b928a24a0020b3764,
title = "Information-bottleneck Based on the Jensen-shannon Divergence with Applications to Pairwise Clustering",
abstract = "The information-bottleneck (IB) principle is defined in terms of mutual information. This study defines mutual information between two random variables using the Jensen-Shannon (JS) divergence instead of the standard definition which is based on the Kullback-Leibler (KL) divergence. We reformulate the information-bottleneck principle using the proposed mutual information and apply it to the problem of pairwise clustering. We show that applying IB to clustering tasks using JS divergences instead of KL yields improved results. This indicates that JS-based mutual information has an expressive power at least as the standard KL-based mutual information.",
keywords = "Jensen-Shannon (JS) divergence, information bottleneck, pairwise clustering",
author = "Jacob Goldberger and Yaniv Opochinsky",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 ; Conference date: 12-05-2019 Through 17-05-2019",
year = "2019",
month = may,
doi = "https://doi.org/10.1109/ICASSP.2019.8683613",
language = "الإنجليزيّة",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3507--3511",
booktitle = "2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings",
address = "الولايات المتّحدة",
}