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cs.LG2025
TimeHF: Billion-Scale Time Series Models Guided by Human Feedback
Yongzhi Qi, Hao Hu, Dazhou Lei +6
Time series neural networks perform exceptionally well in real-world applications but encounter challenges such as limited scalability, poor generalization, and suboptimal zero-sho…
cs.LG2022
Improving Accuracy Without Losing Interpretability: A ML Approach for Time Series Forecasting
Yiqi Sun, Zhengxin Shi, Jianshen Zhang +3
In time series forecasting, decomposition-based algorithms break aggregate data into meaningful components and are therefore appreciated for their particular advantages in interpre…