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Efficient Non-Sampling Graph Neural Networks

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TL;DR

The main idea is to use all the negative samples when optimizing the learning objective to avoid the sampling process, and rearrange the origin loss function into a linear form and take advantage of meticulous mathematical derivation to reduce the complexity of the loss function.

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