A Experimental Study to Invariance of Several Groups Action to the Input of Residual Networks
文献类型：会议论文
| 作者 | Yang XY(杨秀义)1,2 ; Han Z(韩志)2; Tang YD(唐延东)2; Han JD(韩建达)2
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| 出版日期 | 2018 |
| 会议日期 | August 11-13, 2018 |
| 会议地点 | Wuyishan, China |
| 关键词 | Invariance Residual network Group action |
| 页码 | 1263-1267 |
| 英文摘要 | We present a fresh new hypothesis that CNN is insensitive to some variants from input training data example, these variants relate to original training inputs by group actions, and will verify this hypothesis experimentally. This hypothesis means CNNs can generalize well on these variants when training on randomly generated training data and illuminates the paradox Why CNNs fit real and noise data and fail drastically when making predictions for noise data. Our findings suggest the study about generalization theory of CNNs should consider into these invariance of group actions to the input training data samples. |
| 产权排序 | 1 |
| 会议录 | Proceeding of the 2018 IEEE International Conference on Information and Automation
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5386-8069-8 |
| 源URL | [http://ir.sia.cn/handle/173321/23839]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Han JD(韩建达) |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing 100049, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Yang XY,Han Z,Tang YD,et al. A Experimental Study to Invariance of Several Groups Action to the Input of Residual Networks[C]. 见:. Wuyishan, China. August 11-13, 2018. |
入库方式： OAI收割
来源：沈阳自动化研究所
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