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Latent Variable Models in the Era of Industrial Big Data: Extension and Beyond. (arXiv:2208.10847v2 [eess.SY] UPDATED)
Oct. 6, 2022, 1:13 a.m. | Xiangyin Kong, Xiaoyu Jiang, Bingxin Zhang, Jinsong Yuan, Zhiqiang Ge
cs.LG updates on arXiv.org arxiv.org
A rich supply of data and innovative algorithms have made data-driven
modeling a popular technique in modern industry. Among various data-driven
methods, latent variable models (LVMs) and their counterparts account for a
major share and play a vital role in many industrial modeling areas. LVM can be
generally divided into statistical learning-based classic LVM and neural
networks-based deep LVM (DLVM). We first discuss the definitions, theories and
applications of classic LVMs in detail, which serves as both a comprehensive
tutorial …
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