iPiano: Inertial proximal algorithm for nonconvex optimization

P Ochs, Y Chen, T Brox, T Pock - SIAM Journal on Imaging Sciences, 2014 - SIAM
In this paper we study an algorithm for solving a minimization problem composed of a
differentiable (possibly nonconvex) and a convex (possibly nondifferentiable) function. The …

Minimization of for Compressed Sensing

P Yin, Y Lou, Q He, J ** group sparsity
T Adam, R Paramesran - Multidimensional Systems and Signal …, 2019 - Springer
It is widely known that the total variation image restoration suffers from the stair casing
artifacts which results in blocky restored images. In this paper, we address this problem by …

Reweighted sparse subspace clustering

J Xu, K Xu, K Chen, J Ruan - Computer Vision and Image Understanding, 2015 - Elsevier
Motion segmentation and human face clustering are two fundamental problems in computer
vision. The state-of-the-art algorithms employ the subspace clustering scheme when …

Sparse Lq-norm least squares support vector machine with feature selection

YH Shao, CN Li, MZ Liu, Z Wang, NY Deng - Pattern Recognition, 2018 - Elsevier
Least squares support vector machine (LS-SVM) is a popular hyperplane-based classifier
and has attracted many attentions. However, it may suffer from singularity or ill-condition …

Combined higher order non-convex total variation with overlap** group sparsity for impulse noise removal

T Adam, R Paramesran, Y Mingming… - Multimedia Tools and …, 2021 - Springer
A typical approach to eliminate impulse noise is to use the ℓ 1-norm for both the data fidelity
term and the regularization terms. However, the ℓ 1-norm tends to over penalize signal …