“Once-for-All DNNs: Simplifying Design of Efficient Models for Diverse Hardware,” a Presentation from MIT

Song Han, Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, delivers the presentation “Once-for-All DNNs: Simplifying Design of Efficient Models for Diverse Hardware” at the Edge AI and Vision Alliance’s July 2020 Edge AI and Vision Innovation Forum. Han shares his group’s latest research on the automated generation of deep neural network architectures that execute efficiently across diverse hardware targets.

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