no code implementations • NeurIPS 2020 • Corinna Cortes, Mehryar Mohri, Javier Gonzalvo, Dmitry Storcheus
We further implement the algorithm in a popular symbolic gradient computation framework and empirically demonstrate on a number of datasets the benefits of $\almo$ framework versus learning with a fixed mixture weights distribution.
1 code implementation • 4 Jun 2019 • Scott Yak, Javier Gonzalvo, Hanna Mazzawi
We also show results for architecture-independent, task-independent, and out-of-distribution generalization gap prediction tasks.
1 code implementation • 30 Apr 2019 • Charles Weill, Javier Gonzalvo, Vitaly Kuznetsov, Scott Yang, Scott Yak, Hanna Mazzawi, Eugen Hotaj, Ghassen Jerfel, Vladimir Macko, Ben Adlam, Mehryar Mohri, Corinna Cortes
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention.
1 code implementation • 14 Mar 2019 • Vladimir Macko, Charles Weill, Hanna Mazzawi, Javier Gonzalvo
However, once a good building block is found, manual design is still required to assemble the final architecture as a combination of multiple blocks under a predefined parameter budget constraint.
Ranked #63 on Image Classification on CIFAR-100 (using extra training data)