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Norm-based Generalization Bounds for Compositionally Sparse Neural Networks
The dataset used in this paper is a multilayered sparse neural network, specifically a convolutional neural network. -
Generalization bounds for graph convolutional neural networks via Rademacher ...
This paper aims at studying the sample complexity of graph convolutional neural networks (GCNs), by providing tight upper bounds of Rademacher complexity for GCN models with a...
