In another big win for the Department of Computer Science, UBC has been awarded a $1.3 million grant from DARPA, the US government agency researching breakthrough technology in the defence industry.
Learning With Less Labels (LWLL) develops more efficient machine learning by massively reducing the amount of labeled data needed to train accurate models. The three-year contract will be overseen by Leonid Sigal and Frank Wood as principal investigators, and delivered by Dr. Wood’s research group Programming Languages for Artificial Intelligence (PLAI).
As Frank Wood explains, "deep learning is revolutionary but requires huge amounts of labelled training data. Our research under this program is about figuring out ways to make deep learning systems use less data. Leon, myself, and other members of the CRA team have long-standing expertise in leveraging side-information to achieve just this, particularly in visual classification, localization, and segmentation tasks.”