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cs.LG2023
Pruning Before Training May Improve Generalization, Provably
Hongru Yang, Yingbin Liang, Xiaojie Guo +2
It has been observed in practice that applying pruning-at-initialization methods to neural networks and training the sparsified networks can not only retain the testing performance…
cs.LG2023
Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK
Hongru Yang, Ziyu Jiang, Ruizhe Zhang +2
We study training one-hidden-layer ReLU networks in the neural tangent kernel (NTK) regime, where the networks' biases are initialized to some constant rather than zero. We prove t…