Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa

12 Mar 2018 Jie Yang Thomas Drake Andreas Damianou Yoelle Maarek

This paper presents a generic Bayesian framework that enables any deep learning model to actively learn from targeted crowds. Our framework inherits from recent advances in Bayesian deep learning, and extends existing work by considering the targeted crowdsourcing approach, where multiple annotators with unknown expertise contribute an uncontrolled amount (often limited) of annotations... (read more)

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