  AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for
automatically learning high-quality ensembles with minimal expert intervention.
Our framework is inspired by the AdaNet algorithm (Cortes et al., 2017) which
learns the structure of a neural network as an ensemble of subnetworks. We
designed it to: (1) integrate with the existing TensorFlow ecosystem, (2) offer
sensible default search spaces to perform well on novel datasets, (3) present a
flexible API to utilize expert information when available, and (4) efficiently
accelerate training with distributed CPU, GPU, and TPU hardware. The code is
open-source and available at: https://github.com/tensorflow/adanet.
