Results 41 to 50 of about 324,327 (273)

Optimal Conditioning of Quasi-Newton Methods [PDF]

Mathematics of Computation, 1970
Quasi-Newton methods accelerate gradient methods for minimizing a function by approximating the inverse Hessian matrix of the function. Several papers in recent literature have dealt with the generation of classes of approximating matrices as a function of a scalar parameter.
Shanno, D. F., Kettler, P. C.
openaire   +2 more sources

The Role of Chemistry Across Disciplines From Humanities to Life Sciences in Understanding Complexity and Emergence

Angewandte Chemie, EarlyView.
This study explores the origins of life by linking prebiotic chemistry, the emergence of information‐carrying molecules such as RNA and proteins, and philosophical questions about consciousness. The study emphasizes the role of molecular evolution in the Central Dogma and provides insights into the chemical origins of biology and the basis of life's ...
Harald Schwalbe, Josef Wachtveitl, Alexander Heckel, Florian Buhr, Sabrina Toews, Thomas M. Schimmer   +5 more
wiley   +2 more sources

Machine Learning in Quasi-Newton Methods

Axioms
In this article, we consider the correction of metric matrices in quasi-Newton methods (QNM) from the perspective of machine learning theory. Based on training information for estimating the matrix of the second derivatives of a function, we formulate a ...
Vladimir Krutikov, Elena Tovbis, Predrag Stanimirović, Lev Kazakovtsev, Darjan Karabašević   +4 more
doaj   +1 more source

Regularization of limited memory quasi-Newton methods for large-scale nonconvex minimization [PDF]

Mathematical Programming Computation, 2019
This paper deals with regularized Newton methods, a flexible class of unconstrained optimization algorithms that is competitive with line search and trust region methods and potentially combines attractive elements of both.
D. Steck, C. Kanzow
semanticscholar   +1 more source

Comparative Analysis of Accelerated Models for Solving Unconstrained Optimization Problems with Application of Khan’s Hybrid Rule

Mathematics, 2022
In this paper, we follow a chronological development of gradient descent methods and its accelerated variants later on. We specifically emphasise some contemporary approaches within this research field. Accordingly, a constructive overview over the class
Vladimir Rakočević, Milena J. Petrović   +1 more
doaj   +1 more source

Continual Learning With Quasi-Newton Methods

IEEE Access
Catastrophic forgetting remains a major challenge when neural networks learn tasks sequentially. Elastic Weight Consolidation (EWC) attempts to address this problem by introducing a Bayesian-inspired regularization loss to preserve knowledge of ...
Steven Vander Eeckt, Hugo Van Hamme
doaj   +1 more source

Quasi-Newton Methods for Solving Nonlinear Programming Problems [PDF]

Computer Science Journal of Moldova, 1996
In the present paper the problem of constrained equality optimization is reduced to sequential solving a series of problems of quadratic programming. The Hessian of the Lagrangian is approximated by a sequence of symmetric positive definite matrices. The
V.Moraru
doaj  

A Space-Time Absolute Nodal Coordinate Formulation Cable Element and the Study of Its Accuracy and Efficiency

Machines, 2023
In this paper, a space-time absolute nodal coordinate formulation cable (SAC) element forming technique based on the Lagrange family of shape functions is proposed.
Dekun Chen, Kun Li, Nianli Lu, Peng Lan
doaj   +1 more source

Structured Quasi-Newton Methods for Optimization with Orthogonality Constraints [PDF]

SIAM Journal on Scientific Computing, 2018
In this paper, we study structured quasi-Newton methods for optimization problems with orthogonality constraints. Note that the Riemannian Hessian of the objective function requires both the Euclidean Hessian and the Euclidean gradient. In particular, we
Jiang Hu, B. Jiang, Lin Lin, Zaiwen Wen, Ya-Xiang Yuan   +4 more
semanticscholar   +1 more source

Nanothermometry in Living Cells: Physical Limits, Conceptual and Material Challenges

Advanced Functional Materials, EarlyView.
Heat and temperature are fundamental to life. When nanothermometers began probing regions as small as a living cell, they triggered controversial claims of large intracellular temperature gradients. We review physical constraints energy‐conservation, entropy production, thermodynamic fluctuations, and molecular dynamics.
Taras Plakhotnik
wiley   +1 more source