Discrete approximation by variational vector splines for noisy data.
Abdelouahed KouibiaMiguel PasadasPublished in: Math. Comput. Simul. (2009)
Keyphrases
- noisy data
- closed form
- noise tolerant
- free energy
- missing data
- learning from noisy data
- euclidean norm
- cubic spline
- image segmentation
- matrix representation
- feature vectors
- high dimensional
- input data
- taylor series
- missing values
- noise free
- continuous functions
- intrinsic dimensionality
- vector space
- b spline
- high dimensionality
- lower bound
- multiscale
- training data
- gaussian convolution
- database