Hardware-aware Deep Neural Network Design

Tuesday, May 21, 2:10 PM - 2:40 PM
Summit Track: 
Technical Insights I
Mission City B1-B5

A central problem in the deployment of deep neural networks is maximizing accuracy within the compute performance constraints of embedded devices. In this talk, we will discuss approaches to addressing this challenge based on automated network search and adaptation algorithms. These algorithms not only discover neural network models that surpass state-of-the-art accuracy, but are also able to adapt models to achieve efficient implementation on diverse processing platforms for real-world applications.


Peter Vajda

Research Manager, Facebook

Peter Vajda is a Research Manager leading the Mobile Vision efforts at Facebook. Before joining Facebook, he was a Visiting Assistant Professor in Professor Bernd Girod’s group in Stanford University, Stanford, USA. He was working on personalized multimedia system and mobile visual search. Peter completed his Ph.D. with Prof. Touradj Ebrahimi at the Ecole Polytechnique Fédéral de Lausanne (EPFL), Lausanne, Switzerland, 2012.

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