ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
In this study, we focus on investigating a nonsmooth convex optimization problem involving the l 1-norm under a non-negative constraint, with the goal of developing an inverse-problem solver for image ...
Hi, I am implementing a manipulation planning algorithm that requires test-time compute (autograd during test-time sampling). When I run the algorithm together with the SAPIEN environment, I observe ...
Abstract: For the conjugate gradient method to solve the unconstrained optimization problem, given a new interval method to obtain the direction parameters, and a new conjugate gradient algorithm is ...
ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...
This study introduced an efficient method for solving non-linear equations. Our approach enhances the traditional spectral conjugate gradient parameter, resulting in significant improvements in the ...
Abstract: A new algorithm which combines the Quasi-Newton (QN) method and conjugate gradient (CG) method are presented in this paper. It is denoted as $\mathbf{QN}-\mathbf{WAM}+$ method and tested ...
MATLAB package of iterative regularization methods and large-scale test problems. This software is described in the paper "IR Tools: A MATLAB Package of Iterative Regularization Methods and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results