Results 31 to 40 of about 12,602,940 (286)

On Meinardus’ examples for the conjugate gradient method [PDF]

Mathematics of Computation, 2007
The conjugate gradient (CG) method is widely used to solve a positive definite linear system A x = b
openaire   +1 more source

A new family of conjugate gradient methods [PDF]

, 2009
In this paper we develop a new class of conjugate gradient methods for unconstrained optimization problems. A new nonmonotone line search technique is proposed to guarantee the global convergence of these conjugate gradient methods under some mild ...
Shi, Zhen-Jun, Guo, Jinhua
core   +1 more source

Conjugate gradient algorithms for conic functions [PDF]

, 1986
summary:The paper contains a description and an analysis of two modifications of the conjugate gradient method for unconstrained minimization which find a minimum of the conic function after a finite number of steps.
Lukšan, Ladislav
core   +1 more source

A Penalized Linear and Nonlinear Combined Conjugate Gradient Method for the Reconstruction of Fluorescence Molecular Tomography

International Journal of Biomedical Imaging, 2007
Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular ...
Shang Shang, Jing Bai, Xiaolei Song, Hongkai Wang, Jaclyn Lau   +4 more
doaj   +1 more source

A Modified Dai–Liao Conjugate Gradient Method Based on a Scalar Matrix Approximation of Hessian and Its Application

Journal of Mathematics, 2023
We introduce and investigate proper accelerations of the Dai–Liao (DL) conjugate gradient (CG) family of iterations for solving large-scale unconstrained optimization problems.
Branislav Ivanov, Gradimir V. Milovanović, Predrag S. Stanimirović, Aliyu Muhammed Awwal, Lev A. Kazakovtsev, Vladimir N. Krutikov   +5 more
doaj   +1 more source

Nonlinear conjugate gradient methods for unconstrained optimization

, 2020
Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method.
Andrei, Neculai
core   +1 more source

Algorithm for Scaling Variables in Minimization Methods

Algorithms
Eliminating poor scaling of variables of minimized functions is a pressing issue in solving high-dimensional minimization problems where it is impossible to use methods that change the metric of the space with full-scale metric matrices.
Elena Tovbis, Vladimir Krutikov, Lev Kazakovtsev   +2 more
doaj   +1 more source

New Scaled Conjugate Gradient Algorithm for Training Artificial Neural Networks Based on Pure Conjugacy Condition [PDF]

Kirkuk Journal of Science, 2015
Conjugate gradient methods constitute excellent neural network training methods characterized by their simplicity efficiency and their very low memory requirements.
Khalil K. Abbo, Hind H. Mohamed
doaj   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

FEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura, Shin‐ichi Tate, Kyota Yasuda   +2 more
wiley   +1 more source

Diversity and complexity in neural organoids

FEBS Letters, EarlyView.
Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley   +1 more source