On the exact minimization of saturated loss functions for robust regression and subspace estimation.
Fabien LauerPublished in: CoRR (2018)
Keyphrases
- loss function
- robust regression
- pairwise
- linear regression
- support vector
- logistic regression
- regression methods
- density estimation
- multiple models
- kernel regression
- high dimensional data
- projection based m estimator
- image derivatives
- feature extraction
- principal component analysis
- feature space
- objective function
- reproducing kernel hilbert space
- least squares
- machine learning
- low dimensional
- dimensionality reduction
- bundle adjustment
- bayesian networks
- feature selection