AIBullisharXiv – CS AI · Jun 96/10
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FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting
Researchers introduce FAME, a sparse mixture-of-experts framework that dynamically routes time series forecasting tasks to specialized models based on data characteristics. Tested on a production retail dataset with 5,000+ vending machines, the system achieves 12.4% MSE improvement over single-model baselines while using only 1.92 experts per series, demonstrating practical advantages for large-scale commercial forecasting systems.