786 citations · 3k across the 61 of their papers we have counts for
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Learning to Compose Domain-Specific Transformations for Data Augmentation
Alexander J. Ratner, Henry R. Ehrenberg, Zeshan Hussain +2
Data augmentation is a ubiquitous technique for increasing the size of labeled training sets by leveraging task-specific data transformations that preserve class labels. While it i…
YellowFin and the Art of Momentum Tuning
Jian Zhang, Ioannis Mitliagkas
Hyperparameter tuning is one of the most time-consuming workloads in deep learning. State-of-the-art optimizers, such as AdaGrad, RMSProp and Adam, reduce this labor by adaptively…
ShortFuse: Biomedical Time Series Representations in the Presence of Structured Information
Madalina Fiterau, Suvrat Bhooshan, Jason Fries +5
In healthcare applications, temporal variables that encode movement, health status and longitudinal patient evolution are often accompanied by rich structured information such as d…