Lower Bounds and a Near-Optimal Shrinkage Estimator for Least Squares Using Random Projections.
Srivatsan SridharMert PilanciAyfer ÖzgürPublished in: IEEE J. Sel. Areas Inf. Theory (2020)
Keyphrases
- least squares
- random projections
- lower bound
- upper bound
- dimensionality reduction
- compressive sensing
- dimension reduction
- original data
- image reconstruction
- compressed sensing
- objective function
- denoising
- random sampling
- sparse representation
- optimal solution
- principal component analysis
- np hard
- low dimensional
- robust estimation
- optical flow
- high dimensionality
- hash functions
- high dimensional
- worst case
- singular value decomposition
- high dimensional data
- document clustering
- sample size
- similarity search
- preprocessing
- image processing