194 citations · 730 across the 35 of their papers we have counts for
4 papers · 1 filter
The intriguing role of module criticality in the generalization of deep networks
Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi
We study the phenomenon that some modules of deep neural networks (DNNs) are more critical than others. Meaning that rewinding their parameter values back to initialization, while…
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…
MLSys: The New Frontier of Machine Learning Systems
Alexander Ratner, Dan Alistarh, Gustavo Alonso +66
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…
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…