Robust Principal Component Analysis Based on Globally-convergent Iteratively Reweighted Least Squares.
Weihao LiJiulun FanXiaobin ZhiXurui LuoPublished in: AIPR (2022)
Keyphrases
- reweighted least squares
- globally convergent
- robust principal component analysis
- autocalibration
- variational inequalities
- low rank
- global convergence
- newton method
- augmented lagrangian
- machine learning
- convex optimization
- semi supervised
- singular value decomposition
- regression model
- linear combination
- dimensionality reduction
- higher order
- active learning
- pairwise
- computer vision