Name
Abstract | ||
|---|---|---|
A general class of Bayesian lower bounds when the underlying loss function is a Bregman divergence is demonstrated. This class can be considered as an extension of the Weinstein-Weiss family of bounds for the mean squared error and relies on finding a variational characterization of Bayesian risk. The approach allows for the derivation of a version of the Cramér-Rao bound that is specific to a given Bregman divergence. The effectiveness of the new bound is evaluated in the Poisson noise setting. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/SPAWC48557.2020.9154314 | 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) |
Keywords | DocType | ISSN |
Bayesian risk,Bregman loss,Bayesian lower bounds,underlying loss function,mean squared error,variational characterization,Bregman divergence | Conference | 1948-3244 |
ISBN | Citations | PageRank |
978-1-7281-5479-4 | 1 | 0.39 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alex Dytso | 1 | 45 | 20.03 |
| Fauß Michael | 2 | 1 | 0.39 |
| H. V. Poor | 3 | 25411 | 1951.66 |
| Michael Fauss | 4 | 6 | 9.05 |