Results 21 to 30 of about 8,001 (254)
Learning to Optimize Quasi-Newton Methods
CoRR, 2022 Fast gradient-based optimization algorithms have become increasingly essential for the computationally efficient training of machine learning models. One technique is to multiply the gradient by a preconditioner matrix to produce a step, but it is unclear what the best preconditioner matrix is.
Isaac Liao +3 more
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A non-Secant quasi-Newton Method for Unconstrained Nonlinear Optimization
Cogent Engineering, 2022 The Secant equation has long been the foundation of quasi-Newton methods, as updated Hessian approximations satisfy the equation with each iteration. Several publications have lately focused on modified versions of the Secant relation, with promising ...
Issam A.R. Moghrabi
doaj +1 more source
Quasi-Newton methods for atmospheric chemistry simulations: implementation in UKCA UM vn10.8 [PDF]
Geoscientific Model Development, 2018 A key and expensive part of coupled atmospheric chemistry–climate model simulations is the integration of gas-phase chemistry, which involves dozens of species and hundreds of reactions.
E. Esentürk +12 more
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Quasi-Newton Methods, Motivation and Theory [PDF]
SIAM Review, 1977 This paper is an attempt to motivate and justify quasi-Newton methods as useful modifications of Newton's method for general and gradient nonlinear systems of equations. References are given to ample numerical justification; here we give an overview of many of the important theoretical results and each is accompanied by sufficient discussion to make ...
Dennis, J. E. jun., More, Jorge J.
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Positive Definiteness of Symmetric Rank 1 (H-Version) Update for Unconstrained Optimization
مجلة بغداد للعلوم, 2022 Several attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of Hessian matrix (second derivative of the objective function).
Saad Shakir Mahmood +2 more
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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
Advanced Functional Materials, EarlyView.A magnetically assisted snap‐through liquid crystal elastomer transforms photochemical deformation into a high‐power mechanical impulse, enabling remote microneedle actuation and highlighting its potential for future smart livestock intervention systems.
Chae Won Lee +3 more
wiley +1 more source
Operation Limits of Integrated Photo‐Rechargeable Batteries
Advanced Materials, EarlyView.This study elucidates the operational limitations of integrated photo‐rechargeable batteries. We demonstrate that the photo‐charging process is fundamentally restricted not only by material‐to‐material energy level alignment but also by transient capacitive charge accumulation within the cathode framework.
Byung‐Man Kim +6 more
wiley +1 more source
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 +1 more
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An improved quasi-Newton equation on the quasi-Newton methods for unconstrained optimizations
Indonesian Journal of Electrical Engineering and Computer Science, 2021 <span><span>Quasi-Newton methods are a class of numerical methods for </span>solving the problem of unconstrained optimization. To improve the overall efficiency of resulting algorithms, we use the quasi-Newton methods which is interesting for quasi-Newton equation.
Hassan, Basim A. +4 more
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