Quantum coarse-graining for extreme dimension reduction in modelling stochastic temporal dynamics.
Thomas J. ElliottPublished in: CoRR (2021)
Keyphrases
- dimension reduction
- feature extraction
- principal component analysis
- linear discriminant analysis
- variable selection
- data mining and machine learning
- high dimensional problems
- low dimensional
- high dimensional data
- singular value decomposition
- high dimensional
- feature space
- high dimensionality
- unsupervised learning
- random projections
- manifold learning
- discriminative information
- partial least squares
- high dimensional data analysis
- feature selection
- dimension reduction methods
- data sets
- sparse metric learning
- cluster analysis
- dimensionality reduction
- preprocessing
- discriminant analysis
- least squares
- association rules
- data analysis