2 papers
cs.CL2020
Unsupervised Data Augmentation with Naive Augmentation and without Unlabeled Data
David Lowell, Brian E. Howard, Zachary C. Lipton +1
Unsupervised Data Augmentation (UDA) is a semi-supervised technique that applies a consistency loss to penalize differences between a model's predictions on (a) observed (unlabeled…
cs.LG2018
Practical Obstacles to Deploying Active Learning
David Lowell, Zachary C. Lipton, Byron C. Wallace
Active learning (AL) is a widely-used training strategy for maximizing predictive performance subject to a fixed annotation budget. In AL one iteratively selects training examples…