13 citations · 32 across the 5 of their papers we have counts for
4 papers
Towards Task and Architecture-Independent Generalization Gap Predictors
Scott Yak, Javier Gonzalvo, Hanna Mazzawi
Can we use deep learning to predict when deep learning works? Our results suggest the affirmative. We created a dataset by training 13,500 neural networks with different architectu…
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles
Charles Weill, Javier Gonzalvo, Vitaly Kuznetsov +9
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention. Our framework is inspire…
Improving Neural Architecture Search Image Classifiers via Ensemble Learning
Vladimir Macko, Charles Weill, Hanna Mazzawi +1
Finding the best neural network architecture requires significant time, resources, and human expertise. These challenges are partially addressed by neural architecture search (NAS)…
Non-Adaptive Learning a Hidden Hipergraph
Hasan Abasi, Nader H. Bshouty, Hanna Mazzawi
We give a new deterministic algorithm that non-adaptively learns a hidden hypergraph from edge-detecting queries. All previous non-adaptive algorithms either run in exponential tim…