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EXTENDING FINITE RANK DEEP KERNEL LEARNING TO FORECASTING OVER LONG TIME HORIZONS
EXTENDING FINITE RANK DEEP KERNEL LEARNING TO FORECASTING OVER LONG TIME HORIZONS
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机译:延长有限排名深核学习,以预测长期视野
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摘要
In one embodiment a finite rank deep kernel learning method includes: receiving a training dataset; forming a plurality of training data subsets from the training dataset; for each respective training data subset of the plurality of training data subsets: calculating a subset-specific loss based on a loss function and the respective training data subset; and optimizing a model based on the subset-specific loss; determining a set of embeddings based on the optimized model; determining, based on the set of embeddings, a plurality of dot kernels; combining the plurality of dot kernels to form a composite kernel for a Gaussian process; receiving live data from an application; and predicting a plurality of values and a plurality of uncertainties associated with the plurality of values simultaneously using the composite kernel.
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