Subspace segmentation with a large number of subspaces using infinity norm minimization
Spectral-clustering based methods have recently attracted considerable attention in the field
of subspace segmentation. The approximately block-diagonal graphs achieved by this kind …
of subspace segmentation. The approximately block-diagonal graphs achieved by this kind …
Investigating customization strategies and convergence behaviors of task-specific ADMM
Alternating Direction Method of Multiplier (ADMM) has been a popular algorithmic
framework for separable optimization problems with linear constraints. For numerical ADMM …
framework for separable optimization problems with linear constraints. For numerical ADMM …
Task embedded coordinate update: a realizable framework for multivariate non-convex optimization
We in this paper propose a realizable framework TECU, which embeds task-specific
strategies into update schemes of coordinate descent, for optimizing multivariate non …
strategies into update schemes of coordinate descent, for optimizing multivariate non …
A nonlocal model with regression predictor for saliency detection and extension
Estimating salient object regions automatically has enhanced many computer vision
applications in recent years. By observing the intrinsic sparsity of saliency map, we propose …
applications in recent years. By observing the intrinsic sparsity of saliency map, we propose …
Learning an Alternating Bergman Network for Non-convex and Non-smooth Optimization Problems
Recently, non-convex and non-smooth problems have received considerable interests in the
fields of image processing and machine learning. The proposed conventional algorithms …
fields of image processing and machine learning. The proposed conventional algorithms …