Search Results - subject:"Autoencoder"

AE-ACG : a novel deep learning-based method for stock price movement prediction

Li, Shicheng; Huang, Xiaoyong; Cheng, Zhonghou; Zou, Wei; … - In: Finance research letters 58 (2023) 1, pp. 1-14

Persistent link: https://www.econbiz.de/10014581306

LSAE : autoencoder latent space for dimensionality reduction-based approach for COVID-19 classification and detection task using vhest X-ray

Bouchlaghem, Younes; Akhiate, Yassine; Touchanti, Kaouthar - In: Operations research forum 4 (2023) 4, pp. 1-23

Persistent link: https://www.econbiz.de/10014441082

A stacking denoising auto-encoder with sample weight approach for order remaining completion time prediction in complex discrete manufacturing workshop

Liu, Daoyuan; Guo, Yu; Huang, Shaohua; Fang, Weiguang; … - In: International journal of production research 61 (2023) 10, pp. 3246-3259

Persistent link: https://www.econbiz.de/10014323607

Deep learning in marketing : a review and research agenda

Liu, Xiao - In: Artificial intelligence in marketing, (pp. 239-271). 2023

Persistent link: https://www.econbiz.de/10014307159

A novel hybrid approach for rice plant disease detection based on stacked autoencoder and convolutional neural network model

Agrawal, Manoj; Agrawal, Shweta - In: International journal of services, economics and management 14 (2023) 3, pp. 321-344

Persistent link: https://www.econbiz.de/10014311696

Deep embedding kernel mixture networks for conditional anomaly detection in high-dimensional data

Kim, Hyojoong; Kim, Heeyoung - In: International journal of production research 61 (2023) 4, pp. 1101-1113

Persistent link: https://www.econbiz.de/10014226944

Forecasting the dynamic correlation of stock indices based on deep learning method

Ni, Jian; Xu, Yue - In: Computational economics 61 (2023) 1, pp. 35-55

Persistent link: https://www.econbiz.de/10014228395

Autoencoder-based three-factor model for the yield curve of Japanese government bonds and a trading strategy

Suimon, Yoshiyuki; Sakaji, Hiroki; Izumi, Kiyoshi; … - In: Journal of Risk and Financial Management 13 (2020) 4, pp. 1-21

machine learning approach of an autoencoder. In addition, we focus on the model parameters of the intermediate layer of the … neural network that constitute the autoencoder and confirm that the three automatically generated factors represent the … bonds by setting their valuation with the autoencoder, and we confirm good performance compared with the trend …

Persistent link: https://www.econbiz.de/10012611310

Autoencoder-based three-factor model for the yield curve of Japanese government bonds and a trading strategy

Suimon, Yoshiyuki; Sakaji, Hiroki; Izumi, Kiyoshi; … - In: Journal of risk and financial management : JRFM 13 (2020) 4/82, pp. 1-21

Persistent link: https://www.econbiz.de/10012302728

unFEAR : unsupervised feature extraction clustering with an application to crisis regimes classification

Chan-Lau, Jorge A.; Wang, Ran - 2020

novel mode contrastive autoencoder to group episodes into time-invariant non-overlapping clusters, each of which could be …

Persistent link: https://www.econbiz.de/10012392653