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Loss meta-learning for forecasting
Meta-learning of loss functions for supervised learning has been used to date for classification tasks, or as a way to enable few-shot learning.
CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting
This paper introduces CloudLSTM, a new branch of recurrent neural models tailored to forecasting over data streams generated by geospatial point-cloud sources.
Multi-Service Mobile Traffic Forecasting via Convolutional Long Short-Term Memories
Network slicing is increasingly used to partition network infrastructure between different mobile services.
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