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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Bibliographic Details
Main Authors: Zhuang, Huiping, Weng, Zhenyu, Xie, Renchunzi, Toh, Kar-Ann, Lin, Zhiping
Other Authors: School of Electrical and Electronic Engineering
Format: Conference Paper
Language:English
Published: 2024
Subjects:
Computer and Information Science
Class-incremental learning
Data privacy
Online Access:https://hdl.handle.net/10356/174481
https://proceedings.neurips.cc/paper_files/paper/2022

Internet

https://hdl.handle.net/10356/174481
https://proceedings.neurips.cc/paper_files/paper/2022

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