AdaNet: Adaptive Structural Learning of Artificial Neural Networks

Code

• github.com/dataforcast/OC_Datascientist
  tf★ 0
• github.com/MS-Mind/MS-Code-03
  mindspore★ 0

Abstract

We present new algorithms for adaptively learning artificial neural networks. Our algorithms (AdaNet) adaptively learn both the structure of the network and its weights. They are based on a solid theoretical analysis, including data-dependent generalization guarantees that we prove and discuss in detail. We report the results of large-scale experiments with one of our algorithms on several binary classification tasks extracted from the CIFAR-10 dataset. The results demonstrate that our algorithm can automatically learn network structures with very competitive performance accuracies when compared with those achieved for neural networks found by standard approaches.

Tasks

Reproductions