Products with variables from low-dimensional affine spaces and shifted power identity testing in finite fields.
Igor E. ShparlinskiPublished in: J. Symb. Comput. (2014)
Keyphrases
- low dimensional
- high dimensional
- high dimensional data
- dimensionality reduction
- variable selection
- low dimensional manifolds
- principal component analysis
- latent space
- manifold learning
- power consumption
- low dimensional spaces
- input space
- finite dimensional
- affine invariant
- affine transformation
- data points
- real numbers
- embedding space
- linear dimensionality reduction
- random variables
- independent variables
- multidimensional scaling
- product information
- vector space
- function symbols
- dimension reduction
- finite sets
- semi supervised
- euclidean space
- gaussian process latent variable models
- image processing