Finite sample performance of least squares estimation in sub-Gaussian noise.
Michael KrikheliAmir LeshemPublished in: SSP (2016)
Keyphrases
- gaussian noise
- finite sample
- sample size
- denoising
- statistical learning theory
- uniform convergence
- noisy images
- nearest neighbor
- image restoration
- error bounds
- noise level
- impulse noise
- signal to noise ratio
- noise removal
- parzen window
- statistical learning
- generalization error
- machine learning
- support vector machine
- theoretical analysis
- image denoising
- model selection
- learning problems
- generalization bounds
- probability distribution
- error rate
- high dimensional
- computer vision