Reconciling ''priors'' and ''priors'' without prejudice ?
Overview & Synopsis
We discuss a long-lasting {\em qui pro quo} between regularization-based and Bayesian-based approaches to inverse problems, and review some recent results that try to reconcile both viewpoints. This sheds light on some tradeoff between computational efficiency and estimation accuracy in sparse regularization.
Indexed from repository: HAL Open Science
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hal.science)
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Document Information
| Document Title | Reconciling ''priors'' and ''priors'' without prejudice ? |
|---|---|
| Author / Organization | Rémi Gribonval |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2013 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-224938 |
| Original Source Link | Visit Source Page on hal.science » |