SAILOR: Structural Augmentation Based Tail Node Representation Learning vs Photo to Video

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SAILOR: Structural Augmentation Based Tail Node Representation Learning
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SAILOR: Structural Augmentation Based Tail Node Representation Learning

In the pursuit of promoting the expressiveness of GNNs for tail nodes, we explore how the deficiency of structural information deteriorates the performance of tail nodes and propose a general Structural Augmentation based taIL nOde Representation learning framework, dubbed as SAILOR, which can jointly learn to augment the graph structure and extract more informative representations for tail nodes.

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Photo to Video
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Photo to Video

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