High-Dimensional Sparse Bayesian Learning without Covariance Matrices.
Alexander LinAndrew H. SongBerkin BilgicDemba E. BaPublished in: ICASSP (2022)
Keyphrases
- covariance matrices
- sparse bayesian learning
- high dimensional
- covariance matrix
- maximum likelihood
- vector space
- low dimensional
- noisy data
- gaussian distribution
- distance measure
- gaussian mixture model
- dimensionality reduction
- similarity search
- sparse learning
- high dimensionality
- high dimensional data
- gaussian mixture
- feature space
- parameter space
- relevance vector machine
- principal component analysis
- em algorithm
- linear classifiers
- multi task
- probability density function
- data points
- transformation matrix
- nearest neighbor
- data sets
- expectation maximization