49 citations · 79 across the 7 of their papers we have counts for
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stat.ML2019
Benign Overfitting in Linear Regression
Peter L. Bartlett, Philip M. Long, Gábor Lugosi +1
The phenomenon of benign overfitting is one of the key mysteries uncovered by deep learning methodology: deep neural networks seem to predict well, even with a perfect fit to noisy…
cs.LG2019
Generalization bounds for deep convolutional neural networks
Philip M. Long, Hanie Sedghi
We prove bounds on the generalization error of convolutional networks. The bounds are in terms of the training loss, the number of parameters, the Lipschitz constant of the loss an…
cs.LG2019
On the effect of the activation function on the distribution of hidden nodes in a deep network
Philip M. Long, Hanie Sedghi
We analyze the joint probability distribution on the lengths of the vectors of hidden variables in different layers of a fully connected deep network, when the weights and biases a…