Deep Convolutional Networks on Graph-Structured Data

CoRR, Volume abs/1506.05163, 2015.

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In contexts where feature similarities can be estimated using unlabeled data, our model has less parameters to learn from labeled data

Abstract:

Deep Learning's recent successes have mostly relied on Convolutional Networks, which exploit fundamental statistical properties of images, sounds and video data: the local stationarity and multi-scale compositional structure, that allows expressing long range interactions in terms of shorter, localized interactions. However, there exist...More

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