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model-training

topic1 events
papersSEP 10 04:00 UTC

Study examines trade-off between forecast horizon length and learnability in autoregressive models

A new study investigates how far into the future autoregressive models should be trained when forecasting dynamical systems. The authors identify a trade-off between predictive performance and learnability as the training horizon grows, suggesting an optimal horizon exists. The findings offer practical guidance for selecting prediction horizons during model training.

forecasting/time-series/autoregressive/training