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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Main Authors: | , , , , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/174481 https://proceedings.neurips.cc/paper_files/paper/2022 |
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Institution: | Nanyang Technological University |
Language: | English |
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