Using swarm intelligence to optimize neural network hyperparameters: comparative analysis on MNIST and CIFAR-10
Journal Title: Modern Innovations, Systems and Technologies - Year 2024, Vol 4, Issue 2
Abstract
Swarm Intelligence offers powerful methods for solving optimization problems used in configuring hyperparameters of neural networks. This article examines the performance of the particle swarm optimization algorithm compared to Grid Search on two different datasets: MNIST and CIFAR-10. Experimental results show that the effectiveness of optimization methods varies depending on the complexity of the task and the data.
Authors and Affiliations
А. А. Inkizhekov, A. S. Dulesov
Keywords
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- EP ID EP755346
- DOI 10.47813/2782-2818-2024-4-2-0291-0297
- Views 56
- Downloads 0
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