Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs.
Jonathan A. KelnerFrederic KoehlerRaghu MekaDhruv RohatgiPublished in: NeurIPS (2022)
Keyphrases
- lower bound
- sparse representation
- branch and bound algorithm
- objective function
- regularized regression
- elastic net
- group lasso
- least squares
- regression model
- branch and bound
- image classification
- rank minimization
- linear combination
- model selection
- sparse data
- compressed sensing
- high dimensional
- generalized linear models
- dense motion estimation
- feature selection