IEICE TRANSACTIONS on Fundamentals
Meta-Bound on Lower Bounds of Bayes Risk in Parameter Estimation
Summary :
Information-theoretic lower bounds of the Bayes risk have been investigated for a problem of parameter estimation in a Bayesian setting. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as mutual information, Sibson's α-mutual information, f-divergence, and Csiszár's f-informativity. In this paper, we introduce an inequality called a “meta-bound for lower bounds of the Bayes risk” and show that the previous results can be derived from this inequality.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E107-A No.3 pp.503-509
- Publication Date
- 2024/03/01
- Publicized
- 2023/08/09
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2023TAP0002
- Type of Manuscript
- Special Section PAPER (Special Section on Information Theory and Its Applications)
- Category
- Estimation
Authors
Shota SAITO
Gunma University
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Shota SAITO, "Meta-Bound on Lower Bounds of Bayes Risk in Parameter Estimation" in IEICE TRANSACTIONS on Fundamentals,
vol. E107-A, no. 3, pp. 503-509, March 2024, doi: 10.1587/transfun.2023TAP0002.
Abstract: Information-theoretic lower bounds of the Bayes risk have been investigated for a problem of parameter estimation in a Bayesian setting. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as mutual information, Sibson's α-mutual information, f-divergence, and Csiszár's f-informativity. In this paper, we introduce an inequality called a “meta-bound for lower bounds of the Bayes risk” and show that the previous results can be derived from this inequality.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2023TAP0002/_p
Copy
@ARTICLE{e107-a_3_503,
author={Shota SAITO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Meta-Bound on Lower Bounds of Bayes Risk in Parameter Estimation},
year={2024},
volume={E107-A},
number={3},
pages={503-509},
abstract={Information-theoretic lower bounds of the Bayes risk have been investigated for a problem of parameter estimation in a Bayesian setting. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as mutual information, Sibson's α-mutual information, f-divergence, and Csiszár's f-informativity. In this paper, we introduce an inequality called a “meta-bound for lower bounds of the Bayes risk” and show that the previous results can be derived from this inequality.},
keywords={},
doi={10.1587/transfun.2023TAP0002},
ISSN={1745-1337},
month={March},}
Copy
TY - JOUR
TI - Meta-Bound on Lower Bounds of Bayes Risk in Parameter Estimation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 503
EP - 509
AU - Shota SAITO
PY - 2024
DO - 10.1587/transfun.2023TAP0002
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E107-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2024
AB - Information-theoretic lower bounds of the Bayes risk have been investigated for a problem of parameter estimation in a Bayesian setting. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as mutual information, Sibson's α-mutual information, f-divergence, and Csiszár's f-informativity. In this paper, we introduce an inequality called a “meta-bound for lower bounds of the Bayes risk” and show that the previous results can be derived from this inequality.
ER -
English
