Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity

NIPS 2020, 2020.

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We proposed the notion of label-awareness to explain the performance gap between a model trained by neural tangent kernel and real-world neural networks

Abstract:

As a popular approach to modeling the dynamics of training overparametrized neural networks (NNs), the neural tangent kernels (NTK) are known to fall behind real-world NNs in generalization ability. This performance gap is in part due to the \textit{label agnostic} nature of the NTK, which renders the resulting kernel not as \textit{loc...More
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