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

• 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

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...