all AI news
Mixture-of-Linear-Experts for Long-term Time Series Forecasting
May 3, 2024, 4:54 a.m. | Ronghao Ni, Zinan Lin, Shuaiqi Wang, Giulia Fanti
cs.LG updates on arXiv.org arxiv.org
Abstract: Long-term time series forecasting (LTSF) aims to predict future values of a time series given the past values. The current state-of-the-art (SOTA) on this problem is attained in some cases by linear-centric models, which primarily feature a linear mapping layer. However, due to their inherent simplicity, they are not able to adapt their prediction rules to periodic changes in time series patterns. To address this challenge, we propose a Mixture-of-Experts-style augmentation for linear-centric models and …
abstract art arxiv cases cs.ai cs.lg current experts feature forecasting future however layer linear long-term mapping series simplicity sota state time series time series forecasting type values
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US