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cs.LG2018
Exploiting Class Learnability in Noisy Data
Matthew Klawonn, Eric Heim, James Hendler
In many domains, collecting sufficient labeled training data for supervised machine learning requires easily accessible but noisy sources, such as crowdsourcing services or tagged…
cs.CV2018
Generating Triples with Adversarial Networks for Scene Graph Construction
Matthew Klawonn, Eric Heim
Driven by successes in deep learning, computer vision research has begun to move beyond object detection and image classification to more sophisticated tasks like image captioning…