ADMM-based hyperspectral unmixing networks for abundance and endmember estimation
Hyperspectral image (HSI) unmixing is an increasingly studied problem in various areas,
including remote sensing. It has been tackled using both physical model-based approaches …
including remote sensing. It has been tackled using both physical model-based approaches …
Gpx-admm-net: interpretable deep neural network for image compressive sensing
The building of effective neural network architectures for solving image compressive sensing
(CS) problems is a challenge. Hence, it is helpful to consult the structural insight provided by …
(CS) problems is a challenge. Hence, it is helpful to consult the structural insight provided by …
VAGA: a novel viscosity-based accelerated gradient algorithm: Convergence analysis and applications
Proximal Algorithms are known to be very popular in the area of signal processing, image
reconstruction, variational inequality and convex optimization due to their small iteration …
reconstruction, variational inequality and convex optimization due to their small iteration …
[PDF][PDF] A Lyapunov analysis of FISTA with local linear convergence for sparse optimization
We conduct a Lyapunov analysis of the Fast Iterative Shrinkage and Thresholding Algorithm
(FISTA) and show that the algorithm obtains local linear convergence for the special case of …
(FISTA) and show that the algorithm obtains local linear convergence for the special case of …
Local and global convergence of an inertial version of forward-backward splitting
A problem of great interest in optimization is to minimize a sum of two closed, proper, and
convex functions where one is smooth and the other has a computationally inexpensive …
convex functions where one is smooth and the other has a computationally inexpensive …