Search Results - subject:"Step size"

The continuous stochastic gradient method: part II–application and numerics

Grieshammer, Max; Pflug, Lukas; Stingl, Michael; … - In: Computational Optimization and Applications 87 (2023) 3, pp. 977-1008

In this contribution, we present a numerical analysis of the continuous stochastic gradient (CSG) method, including applications from topology optimization and convergence rates. In contrast to standard stochastic gradient optimization schemes, CSG does not discard old gradient samples from...

Persistent link: https://www.econbiz.de/10015323484

Strong convergent inertial two-subgradient extragradient method for finding minimum-norm solutions of variational inequality problems

Alakoya, Timilehin Opeyemi; Mewomo, Oluwatosin - In: Networks and spatial economics : a journal of … 24 (2024) 2, pp. 425-459

Persistent link: https://www.econbiz.de/10015126925

The continuous stochastic gradient method: part I–convergence theory

Grieshammer, Max; Pflug, Lukas; Stingl, Michael; … - In: Computational Optimization and Applications 87 (2023) 3, pp. 935-976

convergence results, step size rules and algorithmic insights. We consider optimization problems in which the objective function …. While in the original CSG paper convergence of a subsequence was established for a diminishing step size, here, we provide a …

Persistent link: https://www.econbiz.de/10015323504

An adaptive and efficient path planning algorithm for UAV navigation in complex environments

Wang, Yonggang; Wang, Guoliang - In: Computers & operations research : an international journal 185 (2026), pp. 1-18

Persistent link: https://www.econbiz.de/10015543030

Solving quasimonotone and non-monotone variational inequalities

Uzor, V. A.; Alakoya, T. O.; Mewomo, Oluwatosin; … - In: Mathematical methods of operations research : ZOR 98 (2023) 3, pp. 461-498

Persistent link: https://www.econbiz.de/10014514975

The continuous stochastic gradient method: part I–convergence theory

Grieshammer, Max; Pflug, Lukas; Stingl, Michael; … - In: Computational Optimization and Applications 87 (2023) 3, pp. 935-976

Persistent link: https://www.econbiz.de/10015403580

The continuous stochastic gradient method: part II–application and numerics

Grieshammer, Max; Pflug, Lukas; Stingl, Michael; … - In: Computational Optimization and Applications 87 (2023) 3, pp. 977-1008

Persistent link: https://www.econbiz.de/10015403586

A step-size follow-the-leader optimization algorithm with an improved step parameters

Singh, Priyanka; Kottath, Rahul - 2023

local optima is high due to randomness in the step parameter. This paper proposes a step-size follow-the-leader (SFTL …) algorithm with decreasing and increasing step-size combinations. The improved step parameter tunes the search space by … been presented in this paper to show the impact of the dynamic step-size parameter. FTL improvement is verified by testing …

Persistent link: https://www.econbiz.de/10014533154

Good Rents versus Bad Rents : R&D Misallocation and Growth

Aghion, Philippe; Bergeaud, Antonin; Boppart, Timo; … - National Bureau of Economic Research - 2025

knowledge externality. We write down an endogenous growth model with innovation step size and process efficiency as alternative … towards high step size firms but not high process efficiency firms. We then use price and productivity data across firms in … reallocating research toward high step size firms, and more so if high step size firms could freely license their innovations to …

Persistent link: https://www.econbiz.de/10015450945

A stochastic ridesharing user equilibrium model with origin-destination-based ride-matching strategy

Du, Muqing; Zhou, Jiankun; Li, Guoyuan; Tan, Heqing; … - In: Transportation research : an international journal 189 (2024), pp. 1-26

Persistent link: https://www.econbiz.de/10015097216