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Neural Architecture Search (NAS) has become an important direction in automated machine learning. In this talk, we will introduce several of our latest works on differentiable NAS, NAS for detection and, based on which, share our opinions on the future trend of NAS, including exploring a sufficiently large search space, designing fast and stable search methods, and introducing hardware constraints to improve the practical value of the search results. We will also introduce to audience the application of these NAS techniques in smart devices and self-driving scenarios. Our talks will be of interest to the audience that are interested in NAS and desire to apply NAS to research and development scenarios.

Presenters: Fabio Maria Carlucci, Hang Xu, Lingxi Xie

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