Results 21 to 30 of about 39,793 (262)
Ensemble Quasi-Newton HMC [PDF]
Proceedings of The 36th Annual International Symposium on Lattice Field Theory — PoS(LATTICE2018), 2019 We present a modification of the Hybrid Monte Carlo algorithm for tackling the critical slowing down of generating Markov chains of lattice gauge configurations towards the continuum limit. We propose a new method to exchange information within an ensemble of Markov chains, and use it to construct an approximate inverse Hessian matrix of the action ...
Jin, Xiao-Yong, Osborn, James C.
openaire +2 more sources
Algorithms, 2021 Gradient-based methods are popularly used in training neural networks and can be broadly categorized into first and second order methods. Second order methods have shown to have better convergence compared to first order methods, especially in solving ...
S. Indrapriyadarsini +4 more
doaj +1 more source
Practical Inexact Proximal Quasi-Newton Method with Global Complexity Analysis [PDF]
, 2015 Recently several methods were proposed for sparse optimization which make careful use of second-order information [10, 28, 16, 3] to improve local convergence rates.
Scheinberg, Katya, Tang, Xiaocheng
core +1 more source
Fast Converging Implementation of a Region-Based Active Contour Model
Journal of Algorithms & Computational Technology, 2015 PDE-based image segmentation based on the active contour model attracts many researchers due to its high precision of edge detection and the continuity of boundaries.
Haiping Xu, Hanxiang Zheng, Meiqing Wang
doaj +1 more source
Diagonal quasi-Newton updating formula using log-determinant norm [PDF]
, 2015 Quasi-Newton method has been widely used in solving unconstrained optimization problems. The popularity of this method is due to the fact that only the gradient of the objective function is required at each iterate. Since second derivatives (Hessian) are
Chen, Chuei Yee +3 more
core +1 more source
Axioms, 2018 This work studies limited memory preconditioners for linear symmetric positive definite systems of equations. Connections are established between a partial Cholesky factorization from the literature and a variant of Quasi-Newton type preconditioners ...
Benedetta Morini
doaj +1 more source
The algorithms of Broyden-CG for unconstrained optimization problems [PDF]
, 2014 The conjugate gradient method plays an important role in solving large-scaled problems and the quasi-Newton method is known as the most efficient method in solving unconstrained optimization problems.
Ibrahim, Mohd Asrul Hery +3 more
core +1 more source
On exact linesearch quasi-Newton methods for minimizing a quadratic function
, 2017 This paper concerns exact linesearch quasi-Newton methods for minimizing a quadratic function whose Hessian is positive definite. We show that by interpreting the method of conjugate gradients as a particular exact linesearch quasi-Newton method ...
Forsgren, Anders, Odland, Tove
core +1 more source
A Newton-Like Trust Region Method for Large-Scale Unconstrained Nonconvex Minimization
Abstract and Applied Analysis, 2013 We present a new Newton-like method for large-scale unconstrained nonconvex minimization. And a new straightforward limited memory quasi-Newton updating based on the modified quasi-Newton equation is deduced to construct the trust region subproblem, in ...
Yang Weiwei +3 more
doaj +1 more source
Experimental Comparisons of Derivative Free Optimization Algorithms [PDF]
, 2009 In this paper, the performances of the quasi-Newton BFGS algorithm, the NEWUOA derivative free optimizer, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the Differential Evolution (DE) algorithm and Particle Swarm Optimizers (PSO) are ...
D.N. Wilke +9 more
core +4 more sources