Rethinking class orders and transferability in class incremental learning
文献类型：期刊论文
| 作者 | He, Chen1,2; Wang, Ruiping1,2; Chen, Xilin1,2 |
| 刊名 | PATTERN RECOGNITION LETTERS
 |
| 出版日期 | 2022-09-01 |
| 卷号 | 161页码:67-73 |
| 关键词 | Transferability Class incremental learning Class order |
| ISSN号 | 0167-8655 |
| DOI | 10.1016/j.patrec.2022.07.014 |
| 英文摘要 | Class Incremental Learning (CIL), an indispensable ability for open-world applications such as service robots, has received increasing attention in recent years. Although many CIL methods sprouted out, re-searchers usually adopt default class orders, leaving the characteristics of different class orders less vis-ited. In this paper, we rethink class orders in CIL from the following aspects: first, we show from prelimi-nary studies that class orders do have an impact on the performance, and mainstream episodic memory -based CIL methods generally favor an interleaved way of arranging class orders; then, we interpret the phenomena above with transferability and propose transferability measures of class orders, which are in line with the method performance under different class orders; based on that, we propose a Class Order Search Algorithm (COSA) to obtain an optimal class order by finding which one has almost the high-est transferability. Experiments on Group ImageNet and iNaturalist verify the importance of class orders in CIL methods, and demonstrate the effectiveness of our proposed transferability measures and COSA. These findings may help raise more attention to the hardly visited class orders in CIL. (c) 2022 Elsevier B.V. All rights reserved. |
| 资助项目 | Natural Science Foundation of China[U21B2025] ; Natural Science Foundation of China[U19B2036] ; Natural Science Foundation of China[61922080] ; National Key R&D Program of China[2021ZD0111901] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000861037800010 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/19808]  |
| 专题 | 中国科学院计算技术研究所期刊论文 |
| 通讯作者 | Wang, Ruiping |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, CAS, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Chen,Wang, Ruiping,Chen, Xilin. Rethinking class orders and transferability in class incremental learning[J]. PATTERN RECOGNITION LETTERS,2022,161:67-73. |
| APA | He, Chen,Wang, Ruiping,&Chen, Xilin.(2022).Rethinking class orders and transferability in class incremental learning.PATTERN RECOGNITION LETTERS,161,67-73. |
| MLA | He, Chen,et al."Rethinking class orders and transferability in class incremental learning".PATTERN RECOGNITION LETTERS 161(2022):67-73. |
入库方式： OAI收割
来源：计算技术研究所
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