Semi-Supervised Learning by Label Gradient Alignment

Jacob Jackson
Jacob Jackson

arXiv: Learning, 2019.

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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

We present label gradient alignment, a novel algorithm for semi-supervised learning which imputes labels for the unlabeled data and trains on the imputed labels. We define a semantically meaningful distance metric on the input space by mapping a point (x, y) to the gradient of the model at (x, y). We then formulate an optimization problem...More

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