2 papers
cs.LG2024
Reconstructing Deep Neural Networks: Unleashing the Optimization Potential of Natural Gradient Descent
Weihua Liu, Said Boumaraf, Jianwu Li +4
Natural gradient descent (NGD) is a powerful optimization technique for machine learning, but the computational complexity of the inverse Fisher information matrix limits its appli…
cs.NE2024
GARA: A novel approach to Improve Genetic Algorithms' Accuracy and Efficiency by Utilizing Relationships among Genes
Zhaoning Shi, Meng Xiang, Zhaoyang Hai +2
Genetic algorithms have played an important role in engineering optimization. Traditional GAs treat each gene separately. However, biophysical studies of gene regulatory networks r…