A variant of finite-dimensional Tikhonov regularization with a-posteriori parameter choice.
J. Thomas KingA. NeubauerPublished in: Computing (1988)
Keyphrases
- finite dimensional
- reproducing kernel hilbert space
- euclidean space
- regularization parameter
- loss function
- kernel methods
- special case
- vector space
- learning theory
- density estimation
- linear model
- distance measure
- domain adaptation
- kernel function
- parameter space
- low dimensional
- maximum a posteriori
- maximum likelihood
- data dependent
- markov random field