Bayesian regression with input noise for high dimensional data.
Jo-Anne TingAaron D'SouzaStefan SchaalPublished in: ICML (2006)
Keyphrases
- high dimensional data
- input data
- regression problems
- low dimensional
- dimensionality reduction
- high dimensional
- nearest neighbor
- high dimensionality
- high dimensions
- data sets
- input space
- subspace clustering
- data points
- gaussian processes
- similarity search
- data analysis
- dimension reduction
- noisy data
- manifold learning
- missing values
- sparse representation
- lower dimensional
- high dimensional spaces
- clustering high dimensional data
- linear discriminant analysis
- regression model
- low rank
- variable selection
- missing data
- pattern recognition
- text data
- model selection
- input image
- subspace learning
- feature extraction
- nonlinear dimensionality reduction
- machine learning
- gaussian process
- high dimensional datasets
- face recognition