Robert Nowak
Professor, University of Wisconsin-Madison
Abstract
The field of Machine Learning (ML) has advanced considerably in recent years, but mostly in well-defined domains and often using huge amounts of human-labeled training data. Machines can recognize objects in images and translate text, but they must be trained with more images and text than a person can see in nearly a lifetime. The computational complexity of training has been offset by recent technological advances, but the cost of training
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