48 citations · 79 across the 4 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)…
The Compact Linear ee Collider (CLIC): Physics Potential
P. Roloff, R. Franceschini, U. Schnoor +1
The Compact Linear Collider, CLIC, is a proposed ee collider at the TeV scale whose physics potential ranges from high-precision measurements to extensive direct sensitivit…