ACIL: analytic class-incremental learning with absolute memorization and privacy protection

ACIL: analytic class-incremental learning with absolute memorization and privacy protection

Class-incremental learning (CIL) learns a classification model with training data of different classes arising progressively. Existing CIL either suffers from serious accuracy loss due to catastrophic forgetting, or invades data privacy by revisiting used exemplars. Inspired by linear learning fo...

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書目詳細資料
Main Authors:	Zhuang, Huiping, Weng, Zhenyu, Xie, Renchunzi, Toh, Kar-Ann, Lin, Zhiping
其他作者:	School of Electrical and Electronic Engineering
格式:	Conference or Workshop Item
語言:	English
出版:	2024
主題:	Computer and Information Science Class-incremental learning Data privacy
在線閱讀:	https://hdl.handle.net/10356/174481 https://proceedings.neurips.cc/paper_files/paper/2022
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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