Flexible and multi-shift induced dimension reduction algorithms for solving large sparse linear systems.
Martin B. van GijzenGerard L. G. SleijpenJens-Peter M. ZemkePublished in: Numer. Linear Algebra Appl. (2015)
Keyphrases
- dimension reduction
- data mining and machine learning
- sparse linear systems
- principal component analysis
- learning algorithm
- high dimensional data
- machine learning
- high dimensional problems
- variable selection
- manifold learning
- singular value decomposition
- unsupervised learning
- manifold embedding
- random projections
- high dimensionality
- neural network
- maximum likelihood
- data warehouse
- knowledge discovery
- feature space
- feature selection
- data mining
- real world