A regularized interior-point method for constrained linear least squares.
Mohsen DehghaniAndrew LambeDominique OrbanPublished in: INFOR Inf. Syst. Oper. Res. (2020)
Keyphrases
- linear least squares
- interior point methods
- condition number
- total least squares
- coefficient matrix
- least squares
- convex optimization
- regularized least squares
- linear program
- linear programming
- primal dual
- semidefinite programming
- quadratic programming
- solving problems
- computationally intensive
- linear systems
- computer vision
- objective function
- machine learning
- pairwise
- np hard
- special case
- multiscale
- feature extraction
- image processing
- optical flow