Results 21 to 30 of about 10,265,072 (333)

Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise [PDF]

SIAM Journal on Optimization, 2019
In this paper, we develop convergence analysis of a modified line search method for objective functions whose value is computed with noise and whose gradient estimates are inexact and possibly random.
A. Berahas, Liyuan Cao, K. Scheinberg
semanticscholar   +1 more source

Inertial-Based Derivative-Free Method for System of Monotone Nonlinear Equations and Application

IEEE Access, 2020
Iterative methods for solving nonlinear problems are of great importance due to their appearance in various areas of applications. In this paper, based on the inertial effect, we propose two projection derivative-free iterative methods for solving system
Aliyu Muhammed Awwal, Poom Kumam, Lin Wang, Shuang Huang, Wiyada Kumam   +4 more
doaj   +1 more source

Parameterized models for on-line and off-line use [PDF]

, 2011
The Monadic Constraint Programming framework leverages Haskell’s rich static type system and powerful abstraction mechanisms to implement an embedded domain specific language (EDSL) for constraint programming.
A.J. Fernandez, F. Fages, G.J. Duck, K. Marriott, R. Cipriano, S. Peyton Jones, T. Schrijvers   +6 more
core   +1 more source

Hierarchical search strategy for the detection of gravitational waves from coalescing binaries: Extension to post-Newtonian wave forms [PDF]

, 1997
The detection of gravitational waves from coalescing compact binaries would be a computationally intensive process if a single bank of template wave forms (i.e., a one step search) is used.
A. Abramovici, A. Krolak, A. Stuart, B. Owen, C. Bradaschia, C. Cutler, C. W. Helstrom, D. Knuth, J. W. Goodman, K. S. Thorne, L. Milano, L. S. Finn, O. E. Brigham, R. N. Bracewell, R. Y. Rubinstein, S. D. Mohanty, S. D. Mohanty, S. O. Rice, S. O. Rice, S. V. Dhurandhar, T. A. Apostolatos, T. A. Apostolatos, W. H. Press   +22 more
core   +3 more sources

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

Approximating Pareto frontier using a hybrid line search approach [PDF]

, 2010
This is the post-print version of the final paper published in Information Sciences. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting ...
Ajith Abraham, Batanović, Chen, Crina Grosan, Das, Das, Das, Deb, Deb, Ehrgott, Ehrgott, Grosan, Ho, Huband, Jahn, Lewis, Messac, Messac, Messac, Messac, Messac, Messac, Messac, Messac, Messac, Miettinen, Okabe, Ortiz, Protter, Rueda, Ruzika, Sanchis, Sayın, Tripathi, Veldhuizen, Wang   +35 more
core   +3 more sources

A Primal-Dual Algorithm with Line Search for General Convex-Concave Saddle Point Problems

SIAM Journal on Optimization, 2020
In this paper, we propose a primal-dual algorithm with a novel momentum term using the partial gradients of the coupling function that can be viewed as a generalization of the method proposed by Chambolle and Pock in 2016 to solve saddle point problems ...
E. Y. Hamedani, N. Aybat
semanticscholar   +1 more source

A new conjugate gradient method for acceleration of gradient descent algorithms

Moroccan Journal of Pure and Applied Analysis, 2021
An accelerated of the steepest descent method for solving unconstrained optimization problems is presented. which propose a fundamentally different conjugate gradient method, in which the well-known parameter βk is computed by an new formula.
Rahali Noureddine, Belloufi Mohammed, Benzine Rachid   +2 more
doaj   +1 more source

Genetic Line Search [PDF]

, 2001
All unconstrained and many constrained optimization problems involve line searches, i.e. minimizing the value of a certain function along a properly chosen direction. There are several methods for performing such one-dimensional optimization but all of them require that the function be unimodal along the search interval. That may force small step sizes
S. Lozano, J. J. Domínguez, F. Guerrero, K. Smith   +3 more
openaire   +1 more source

A modified BFGS type quasi-Newton method with line search for symmetric nonlinear equations problems

Journal of Computational and Applied Mathematics, 2020
In this paper, using approximate gradient of the norm square metric function, we present an inexact MBFGS method with line search for solving symmetric nonlinear equations, which is a generalization of the MBFGS method proposed by Li and Fukushima (2001)
Weijun Zhou
semanticscholar   +1 more source