Hansen, Lars Kai

Lehn-Schiøler, Tue

Madsen, Kristoffer Hougaard

In the Bayesian modeling framework there is a close relation between regularization and the prior distribution over parameters. For prior distributions in the exponential family, we show that the optimal hyper-parameter, i.e., the optimal strength of regularization, satisfies a simple relation: The expectation of the regularization function, i.e., takes the same value in the posterior and prior distribution. We present three examples: two simulations, and application in fMRI neuroimaging

Online Research Database In Technology

Adaptive regularization of noisy linear inverse problems

http://orbit.dtu.dk/ws/files/2746360/imm4417.pdf

Adaptive regularization of noisy linear inverse problems

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Online Research Database In Technology