Web: http://arxiv.org/abs/2209.07521

Sept. 16, 2022, 1:15 a.m. | Kaiyang Zhou, Yuanhan Zhang, Yuhang Zang, Jingkang Yang, Chen Change Loy, Ziwei Liu

cs.CV updates on arXiv.org arxiv.org

We present a systematic study of domain generalization (DG) for tiny neural
networks, a problem that is critical to on-device machine learning applications
but has been overlooked in the literature where research has been focused on
large models only. Tiny neural networks have much fewer parameters and lower
complexity, and thus should not be trained the same way as their large
counterparts for DG applications. We find that knowledge distillation is a
strong candidate for solving the problem: it outperforms …


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