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On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing †
Distributed hypothesis testing (DHT) has emerged as a significant research area, but the information-theoretic optimality of coding strategies is often typically hard to address. This paper studies the DHT problems under the type-based setting, which is requested from the popular federated learning...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606381/ https://www.ncbi.nlm.nih.gov/pubmed/37895555 http://dx.doi.org/10.3390/e25101434 |
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author | Tong, Xinyi Xu, Xiangxiang Huang, Shao-Lun |
author_facet | Tong, Xinyi Xu, Xiangxiang Huang, Shao-Lun |
author_sort | Tong, Xinyi |
collection | PubMed |
description | Distributed hypothesis testing (DHT) has emerged as a significant research area, but the information-theoretic optimality of coding strategies is often typically hard to address. This paper studies the DHT problems under the type-based setting, which is requested from the popular federated learning methods. Specifically, two communication models are considered: (i) DHT problem over noiseless channels, where each node observes i.i.d. samples and sends a one-dimensional statistic of observed samples to the decision center for decision making; and (ii) DHT problem over AWGN channels, where the distributed nodes are restricted to transmit functions of the empirical distributions of the observed data sequences due to practical computational constraints. For both of these problems, we present the optimal error exponent by providing both the achievability and converse results. In addition, we offer corresponding coding strategies and decision rules. Our results not only offer coding guidance for distributed systems, but also have the potential to be applied to more complex problems, enhancing the understanding and application of DHT in various domains. |
format | Online Article Text |
id | pubmed-10606381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106063812023-10-28 On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing † Tong, Xinyi Xu, Xiangxiang Huang, Shao-Lun Entropy (Basel) Article Distributed hypothesis testing (DHT) has emerged as a significant research area, but the information-theoretic optimality of coding strategies is often typically hard to address. This paper studies the DHT problems under the type-based setting, which is requested from the popular federated learning methods. Specifically, two communication models are considered: (i) DHT problem over noiseless channels, where each node observes i.i.d. samples and sends a one-dimensional statistic of observed samples to the decision center for decision making; and (ii) DHT problem over AWGN channels, where the distributed nodes are restricted to transmit functions of the empirical distributions of the observed data sequences due to practical computational constraints. For both of these problems, we present the optimal error exponent by providing both the achievability and converse results. In addition, we offer corresponding coding strategies and decision rules. Our results not only offer coding guidance for distributed systems, but also have the potential to be applied to more complex problems, enhancing the understanding and application of DHT in various domains. MDPI 2023-10-10 /pmc/articles/PMC10606381/ /pubmed/37895555 http://dx.doi.org/10.3390/e25101434 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tong, Xinyi Xu, Xiangxiang Huang, Shao-Lun On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing † |
title | On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing † |
title_full | On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing † |
title_fullStr | On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing † |
title_full_unstemmed | On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing † |
title_short | On the Optimal Error Exponent of Type-Based Distributed Hypothesis Testing † |
title_sort | on the optimal error exponent of type-based distributed hypothesis testing † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606381/ https://www.ncbi.nlm.nih.gov/pubmed/37895555 http://dx.doi.org/10.3390/e25101434 |
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