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cs.LG2024
Stock Type Prediction Model Based on Hierarchical Graph Neural Network
Jianhua Yao, Yuxin Dong, Jiajing Wang +3
This paper introduces a novel approach to stock data analysis by employing a Hierarchical Graph Neural Network (HGNN) model that captures multi-level information and relational str…
cs.LG2024
Reducing Bias in Deep Learning Optimization: The RSGDM Approach
Honglin Qin, Hongye Zheng, Bingxing Wang +3
Currently, widely used first-order deep learning optimizers include non-adaptive learning rate optimizers and adaptive learning rate optimizers. The former is represented by SGDM (…
cs.LG2024
Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function
Hongye Zheng, Bingxing Wang, Minheng Xiao +3
Adaptive optimizers are pivotal in guiding the weight updates of deep neural networks, yet they often face challenges such as poor generalization and oscillation issues. To counter…