Dimensionality Reduction in Statistical Learning.
Alexander V. BernsteinAlexander P. KuleshovPublished in: ICMLA (2014)
Keyphrases
- statistical learning
- dimensionality reduction
- manifold learning
- diffusion maps
- high dimensionality
- information theory
- high dimensional
- model selection
- statistical learning theory
- low dimensional
- high dimensional data
- unsupervised learning
- pattern recognition
- supervised learning
- feature space
- principal component analysis
- dimensionality reduction methods
- feature extraction
- feature selection
- random projections
- dimension reduction
- data points
- nonlinear dimensionality reduction
- multi view face detection
- semi supervised learning
- linear discriminant analysis
- sparse representation
- real world
- statistical inference
- machine learning
- singular value decomposition
- least squares
- support vector
- training data
- locally linear embedding
- information retrieval
- structured sparsity
- data mining