Výsledky vyhledávání

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Robust Multivariate Time Series Forecasting against Intra- and Inter-Series Transitional Shift

Autor: He, Hui, Zhang, Qi, Yi, Kun, Xue, Xiaojun, Wang, Shoujin, Hu, Liang, Cao, Longbing

The non-stationary nature of real-world Multivariate Time Series (MTS) data presents forecasting models with a formidable challenge of the time-variant distribution of time series, referred to as distribution shift. Existing studies on the distributi

Externí odkaz: http://arxiv.org/abs/2407.13194

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Robust Few-Shot Named Entity Recognition with Boundary Discrimination and Correlation Purification

Autor: Xue, Xiaojun, Zhang, Chunxia, Xu, Tianxiang, Niu, Zhendong

Few-shot named entity recognition (NER) aims to recognize novel named entities in low-resource domains utilizing existing knowledge. However, the present few-shot NER models assume that the labeled data are all clean without noise or outliers, and th

Externí odkaz: http://arxiv.org/abs/2312.07961

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Akademický článek

BOF steelmaking endpoint carbon content and temperature soft sensor model based on supervised weighted local structure preserving projection

Autor: Su YunKe, Liu Hui, Chen FuGang, Liu JianXun, Li Heng, Xue XiaoJun

Publikováno v: High Temperature Materials and Processes, Vol 43, Iss 1, Pp pp. 51-58 (2024)

Endpoint control stands as a pivotal determinant of steel quality. However, the data derived from the BOF steelmaking process are characterized by high dimension, with intricate nonlinear relationships between variables and diverse working conditions

Externí odkaz: https://doaj.org/article/5d24d6f9108749eab9bcb81b2352007c