Precise expressions for random projections: Low-rank approximation and randomized Newton.
Michal DerezinskiFeynman T. LiangZhenyu LiaoMichael W. MahoneyPublished in: NeurIPS (2020)
Keyphrases
- random projections
- low rank approximation
- singular value decomposition
- dimensionality reduction
- subspace learning
- dimension reduction
- sparse representation
- low rank
- principal component analysis
- image reconstruction
- original data
- low dimensional
- hash functions
- spectral clustering
- document clustering
- kernel matrix
- random sampling
- iterative algorithms
- computer vision
- face recognition
- pattern recognition
- neural network
- natural images
- feature space
- matrix factorization
- multiscale
- high resolution
- image classification
- nonnegative matrix factorization
- feature selection
- image features
- least squares