no code implementations • 14 Aug 2020 • Jie Fang, Jian-Wu Lin, Shu-Tao Xia, Yong Jiang, Zhikang Xia, Xiang Liu
This paper proposes Neural Network-based Automatic Factor Construction (NNAFC), a tailored neural network framework that can automatically construct diversified financial factors based on financial domain knowledge and a variety of neural network structures.
no code implementations • 16 Jun 2020 • Jie Fang, Jian-Wu Lin
In this paper, we propose to use neural networks to represent these indicators and train a large network constructed of smaller networks as feature layers to fine-tune the prior knowledge represented by the indicators.
no code implementations • 26 Dec 2019 • Jie Fang, Shu-Tao Xia, Jian-Wu Lin, Zhikang Xia, Xiang Liu, Yong Jiang
This paper proposes Alpha Discovery Neural Network (ADNN), a tailored neural network structure which can automatically construct diversified financial technical indicators based on prior knowledge.
no code implementations • 8 Dec 2019 • Jie Fang, Shu-Tao Xia, Jian-Wu Lin, Yong Jiang
According to neural network universal approximation theorem, pre-training can conduct a more effective and explainable evolution process.
no code implementations • 7 Jun 2019 • Jian-Wu Lin, Hao Li
Most video surveillance systems use both RGB and infrared cameras, making it a vital technique to re-identify a person cross the RGB and infrared modalities.
Cross-Modality Person Re-identification Person Re-Identification