Lower Bounds and a Near-Optimal Shrinkage Estimator for Least Squares using Random Projections.
Srivatsan SridharMert PilanciAyfer ÖzgürPublished in: CoRR (2020)
Keyphrases
- least squares
- random projections
- lower bound
- upper bound
- dimension reduction
- dimensionality reduction
- compressed sensing
- original data
- image reconstruction
- sparse representation
- objective function
- compressive sensing
- np hard
- random sampling
- worst case
- denoising
- principal component analysis
- singular value decomposition
- hash functions
- robust estimation
- low dimensional
- optimal solution
- optical flow
- data mining
- pattern recognition
- unsupervised learning
- sample size