Dimension Reduction of Large Sparse AND-NOT Network Models.
Alan Veliz-CubaBoris AguilarReinhard C. LaubenbacherPublished in: Electron. Notes Theor. Comput. Sci. (2015)
Keyphrases
- dimension reduction
- high dimensional
- principal component analysis
- random projections
- high dimensional problems
- low dimensional
- partial least squares
- manifold learning
- probabilistic model
- sparse representation
- unsupervised learning
- sparse metric learning
- data mining and machine learning
- high dimensional data
- model selection
- data analysis
- training data
- feature extraction
- feature selection
- singular value decomposition
- object recognition
- support vector
- discriminative information
- high dimensional data analysis
- image sequences