Results 31 to 40 of about 1,099,998 (291)
Decentralized Quasi-Newton Methods [PDF]
IEEE Transactions on Signal Processing, 2017 We introduce the decentralized Broyden-Fletcher-Goldfarb-Shanno (D-BFGS) method as a variation of the BFGS quasi-Newton method for solving decentralized optimization problems. The D-BFGS method is of interest in problems that are not well conditioned, making first order decentralized methods ineffective, and in which second order information is not ...
Mark Eisen +2 more
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Greedy Quasi-Newton Methods with Explicit Superlinear Convergence [PDF]
SIAM Journal on Optimization, 2020 In this paper, we study greedy variants of quasi-Newton methods. They are based on the updating forulas from a certain subclass of the Broyden family. In particular, this subclass includes the well-known DFP, BFGS ans SR1 updates. However, in contrast to
Anton Rodomanov, Y. Nesterov
semanticscholar +1 more source
THE NEW RANK ONE CLASS FOR UNCONSTRAINED PROBLEMS SOLVING
Science Journal of University of Zakho, 2023 One of the most well-known methods for unconstrained problems is the quasi-Newton approach, iterative solutions. The great precision and quick convergence of the quasi-Newton methods are well recognized. In this work, the new algorithm for the symmetric
Ahmed Mustafa
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Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization [PDF]
Mathematical Programming Computation, 2021 We consider unconstrained stochastic optimization problems with no available gradient information. Such problems arise in settings from derivative-free simulation optimization to reinforcement learning. We propose an adaptive sampling quasi-Newton method
Raghu Bollapragada, Stefan M. Wild
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Quasi-Newton Methods for Saddle Point Problems and Beyond [PDF]
Neural Information Processing Systems, 2021 This paper studies quasi-Newton methods for solving strongly-convex-strongly-concave saddle point problems (SPP). We propose greedy and random Broyden family updates for SPP, which have explicit local superlinear convergence rate of ${\mathcal O}\big ...
Chengchang Liu, Luo Luo
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On the Convergence Rate of Quasi-Newton Methods on Strongly Convex Functions with Lipschitz Gradient
Mathematics, 2023 The main results of the study of the convergence rate of quasi-Newton minimization methods were obtained under the assumption that the method operates in the region of the extremum of the function, where there is a stable quadratic representation of the ...
Vladimir Krutikov +3 more
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A New Globally Convergent Self-Scaling Vm Algorithm for Convex and Nonconvex Optimization [PDF]
Kirkuk Journal of Science, 2011 In unconstrained optimization, the original quasi-Newton condition where is the difference of the gradients at two successive iterations. Li and Fukushima proposed a modified BFGS methods based on a new Quasi –Newton equation where , where is a
Abbas Y. AL-Bayati, Basim A. Hassan
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Rates of superlinear convergence for classical quasi-Newton methods [PDF]
Mathematical programming, 2020 We study the local convergence of classical quasi-Newton methods for nonlinear optimization. Although it was well established a long time ago that asymptotically these methods converge superlinearly, the corresponding rates of convergence still remain ...
Anton Rodomanov, Y. Nesterov
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Phase field fracture modelling using quasi-Newton methods and a new adaptive step scheme [PDF]
Theoretical and applied fracture mechanics (Print), 2019 We investigate the potential of quasi-Newton methods in facilitating convergence of monolithic solution schemes for phase field fracture modelling. Several paradigmatic boundary value problems are addressed, spanning the fields of quasi-static fracture ...
Philip K. Kristensen +1 more
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Surrogate-based acceleration of quasi-Newton techniques for fluid-structure interaction simulations
Computers & structures, 2022 Quasi-Newton methods have proven to be an efficient way to couple partitioned solvers in fluid-structure interaction problems, as they are able to stabilize cases with high added-mass, as well as accelerate the convergence.
N. Delaissé +3 more
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