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Power to the People: The Role of Humans in Interactive Machine Learning

Creator:

Amershi, Saleema, Cakmak, Maya, Knox, W. Bradley, and Kulesza, Todd

Abstract:

Systems that can learn interactively from their end-users are quickly becoming widespread. Until recently, this progress has been fueled mostly by advances in machine learning; however, more and more researchers are realizing the importance of studying users of these systems. In this article we promote this approach and demonstrate how...

Resource Type:

Article