Feb. 26, 2024, 5:44 a.m. | Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang, Bryan Hooi, Roger Zimmermann

cs.LG updates on arXiv.org arxiv.org

arXiv:2310.09751v3 Announce Type: replace
Abstract: Multivariate time series forecasting plays a pivotal role in contemporary web technologies. In contrast to conventional methods that involve creating dedicated models for specific time series application domains, this research advocates for a unified model paradigm that transcends domain boundaries. However, learning an effective cross-domain model presents the following challenges. First, various domains exhibit disparities in data characteristics, e.g., the number of variables, posing hurdles for existing models that impose inflexible constraints on these factors. …

abstract application arxiv contrast cs.lg domain domains forecasting language multivariate paradigm pivotal research role series technologies time series time series forecasting type unified model web

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