Whiplash Gradient Descent Algorithm
Versión 2.3 (475 KB) por
Subhransu Sekhar Bhattacharjee
First Order Gradient Descent Algorithm for Stiff-systems.
Whiplash Gradient Descent: A Closed Loop Gradient Descent Algorithm applied to Rosenbrock's function. Please find the paper here: https://arxiv.org/abs/2108.12883.
We introduce a novel adaptive damping technique for an inertial gradient system which finds application as a gradient descent algorithm for unconstrained optimisation. In an example using the non-convex Rosenbrock's function, we show an improvement on existing momentum-based gradient optimisation methods. Also using Lyapunov stability analysis, we demonstrate the performance of the continuous-time version of the algorithm. Using numerical simulations, we consider the performance of its discrete-time counterpart obtained by using the symplectic Euler method of discretisation.
This file contains a live MATLAB example and a Simulink simulation by Mr. Subhransu Sekhar Bhattacharjee, U7143478, ANU, developed under the supervision of Prof. Dr. Ian R. Petersen FAA, College of Engineering and Computer Science, ANU. Please direct any queries regarding the code to Mr. Subhransu Bhattacharjee at u7143478@anu.edu.au. Please use MATLAB version 2021a for running the .mlx file.
Citar como
Subhransu Sekhar Bhattacharjee & Ian R Petersen, A Closed Loop Gradient Descent Algorithm applied to Rosenbrock's function, Proceedings of the ANZCC 2021, IEEE Xplore, https://github.com/SubhransuSekharBhattacharjee-01/Whiplash, GitHub.
Compatibilidad con la versión de MATLAB
Se creó con
R2021a
Compatible con cualquier versión
Compatibilidad con las plataformas
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Versión | Publicado | Notas de la versión | |
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2.3 | citation updated |
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2.2 | Note |
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2.1 | paper link added |
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2.0.3 | Description |
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2.0.2 | Summary |
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2.0.1 | Notes |
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2.0.0 | Fixed README |
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1.0.0 |
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