Minimum Variance Estimation of a Sparse Vector within the Linear Gaussian Model: An RKHS Approach
Alexander JungSebastian SchmutzhardFranz HlawatschZvika Ben-HaimYonina C. EldarPublished in: CoRR (2013)
Keyphrases
- kernel methods
- minimum variance
- gaussian model
- reproducing kernel hilbert space
- linear prediction
- machine learning
- gaussian distribution
- support vector machine
- image intensity
- estimation error
- high dimensional
- skin color
- sparse representation
- conditional independence
- feature vectors
- gaussian mixture model
- portfolio optimization
- prediction error
- mixture model
- language model