L2 error estimates for polynomial discrete penalized least-squares approximation on the sphere from noisy data.
Kerstin HesseQuoc Thong Le GiaPublished in: J. Comput. Appl. Math. (2022)
Keyphrases
- noisy data
- error estimates
- least squares
- error analysis
- error estimation
- cross validation
- noise tolerant
- missing data
- noise free
- provably correct
- learning from noisy data
- model selection
- optical flow
- high dimensional
- input data
- missing values
- maximum likelihood
- high dimensionality
- training data
- artificial intelligence
- randomized approximation
- database
- generalization error
- software engineering
- feature vectors
- decision trees
- neural network