Improving Replay Sample Selection and Storage for Less Forgetting in Continual Learning-Reference-Cited by-同舟云学术

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Improving Replay Sample Selection and Storage for Less Forgetting in Continual Learning

Published:2023-10-02 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
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Author:

Brignac Daniel¹,Lobo Niels²,Mahalanobis Abhijit¹

Affiliation:

1. University of Arizona,Tucson,Arizona

2. University of Central Florida,Orlando,Florida

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10350357/10350360/10350558.pdf?arnumber=10350558

Reference46 articles.

1. Online continual learning with maximal interfered retrieval;Aljundi,2019

2. Gradient based sample selection for online continual learning;Aljundi;Advances in neural information processing systems,2019

3. On the effectiveness of lipschitz-driven rehearsal in continual learning;Bonicelli;Advances in Neural Information Processing Systems,2022

4. Dark experience for general continual learning: a strong, simple baseline;Buzzega;Advances in neural information processing systems,2020

5. New insights on reducing abrupt representation change in online continual learning;Caccia

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sketch-Based Replay Projection for Continual Learning;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Low Resource Language Adaptation using Two-stage Regularization for Multilingual ASR;2024 International Conference on Asian Language Processing (IALP);2024-08-04

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