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The graph Laplacian regularization term is usually used in semi-supervised representation learning to provide graph structure information for a model $f(X)$.
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When does label smoothing help?
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Graph Agreement Models for Semi-Supervised Learning
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Be your own teacher: Improve the performance of convolutional neural networks via self distillation
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Graph Neural Networks Exponentially Lose Expressive Power for Node Classification
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