BS-NAS: Broadening-and-Shrinking One-Shot NAS with Searchable Numbers of Channels

22 Mar 2020 Zan Shen Jiang Qian Bojin Zhuang Shaojun Wang Jing Xiao

One-Shot methods have evolved into one of the most popular methods in Neural Architecture Search (NAS) due to weight sharing and single training of a supernet. However, existing methods generally suffer from two issues: predetermined number of channels in each layer which is suboptimal; and model averaging effects and poor ranking correlation caused by weight coupling and continuously expanding search space... (read more)

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