Amir Rosenfeld

Intriguing Properties of Randomly Weighted Networks: Generalizing While Learning Next to Nothing

2019

Training deep neural networks results in strong learned representations that show good generalization capabilities. In most cases, training involves iterative modification of all weights in the network via back-propagation. In Extreme Learning Machines, it has …

A Constructive Prediction of the Generalization Error Across Scales

2020 · International Conference on Learning Representations

The dependency of the generalization error of neural networks on model and dataset size is of critical importance both in practice and for understanding the theory of neural networks. Nevertheless, the functional form of this …