Spectral dimensionality reduction for HMMs
Dean P. FosterJordan RoduLyle H. UngarPublished in: CoRR (2012)
Keyphrases
- dimensionality reduction
- hidden markov models
- high dimensional
- principal component analysis
- data representation
- high dimensionality
- high dimensional data
- low dimensional
- feature selection
- pattern recognition
- principal components
- data points
- pattern recognition and machine learning
- feature space
- feature extraction
- spectral analysis
- structure preserving
- linear discriminant analysis
- dimension reduction
- manifold learning
- dimensionality reduction methods
- nonlinear dimensionality reduction
- linear dimensionality reduction
- multi stream
- hyperspectral imagery
- spectral data
- random projections
- hyperspectral
- nearest neighbor
- hidden states
- supervised dimensionality reduction
- data sets
- chinese named entity recognition
- locally linear embedding
- multidimensional scaling
- kernel learning
- multispectral images
- semi supervised
- image data
- neural network