Scientists in Belgium—that celebrated bastion of ancient beer culture—are harnessing genetic breakthroughs and machine ...
Abstract: In modern industry, fault diagnosis is critical for ensuring production safety and efficiency. Intelligent fault diagnosis methods often suffer performance degradation under varying ...
Abstract: Knowledge distillation (KD), a learning manner with a larger teacher network guiding a smaller student network, transfers dark knowledge from the teacher to the student via logits or ...
Dataset distillation aims to synthesize a small dataset from a large dataset, enabling the model trained on it to perform well on the original dataset. With the blooming of large language models and ...
Photographs available: (UK images and world images) This weekend in St Leonards-On-Sea, East Sussex, a striking new mural will be unveiled to celebrate a landmark moment for global ocean protection:… ...
In this paper, We propose a novel methodology of Wasserstein distance based knowledge distillation (WKD), extending beyond the classical Kullback-Leibler divergece based one pioneered by Hinton et al.
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