Learning to Compose Domain-Specific Transformations for Data Augmentation

• Published in: Advances in neural information processing systems Vol. 30; p. 3239
• Main Authors: Ratner, Alexander J, Ehrenberg, Henry R, Hussain, Zeshan, Dunnmon, Jared, Ré, Christopher
• Format: Journal Article
• Language: English
• Published: United States 01.12.2017

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 is often easy for domain experts to specify individual transformations, constructing and tuning the more sophisticated co...