An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation

28 Feb 2020Makoto TakamotoYusuke MorishitaHitoshi Imaoka

Compressing deep neural network (DNN) models becomes a very important and necessary technique for real-world applications, such as deploying those models on mobile devices. Knowledge distillation is one of the most popular methods for model compression, and many studies have been made on developing this technique... (read more)

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