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GTC ON-DEMAND

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Abstract:

The recent success of deep learning has been driven by the ability to combine significant GPU resources with extremely large labeled datasets. However, many labels are extremely expensive to obtain or even impossible to obtain more than one, such as a specific astronomical event or scientific experiment. By combining vast amounts of labeled surrogate data with advanced few-shot learning, we have demonstrated success in leveraging small data in deep learning. In this talk, we will discuss these exciting results and explore the scientific innovations that made this possible.

The recent success of deep learning has been driven by the ability to combine significant GPU resources with extremely large labeled datasets. However, many labels are extremely expensive to obtain or even impossible to obtain more than one, such as a specific astronomical event or scientific experiment. By combining vast amounts of labeled surrogate data with advanced few-shot learning, we have demonstrated success in leveraging small data in deep learning. In this talk, we will discuss these exciting results and explore the scientific innovations that made this possible.

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Topics:
HPC and AI
Type:
Talk
Event:
Supercomputing
Year:
2018
Session ID:
SC1822
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