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Abstract: In the realm of time series forecasting, traditional models often struggle to effectively manage the intricate dependencies and high dimensionality inherent in multivariate data samples.

However, the selection of initial values and step sizes affects the convergence of the Gauss−Newton method, while the fixed threshold used in fitting impacts the accuracy of sample selection. These ...

Methods such as Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO) have proven effective. However, they still require iterative training, which is often ...

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