Denoising with kernel prediction and asymmetric loss functions.
Thijs VogelsFabrice RousselleBrian McWilliamsGerhard RöthlinAlex HarvillDavid AdlerMark MeyerJan NovákPublished in: ACM Trans. Graph. (2018)
Keyphrases
- loss function
- denoising
- reproducing kernel hilbert space
- support vector
- pairwise
- image denoising
- prediction accuracy
- squared error
- loss minimization
- learning to rank
- kernel classifiers
- kernel function
- risk minimization
- square loss
- logistic regression
- least squares support vector machine
- kernel methods
- total variation
- convex loss functions
- image processing
- multi class
- hinge loss
- gaussian kernels
- gradient boosting
- boosting algorithms
- multiple kernel learning
- support vector machine
- special case
- feature vectors
- feature space
- learning algorithm