Class-incremental Learning for Time Series: Benchmark and Evaluation-Reference-Cited by-同舟云学术

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Class-incremental Learning for Time Series: Benchmark and Evaluation

Published:2024-08-24 Issue: Volume:33 Page:5613-5624
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Qiao Zhongzheng¹^ORCID,Pham Quang²^ORCID,Cao Zhen²^ORCID,Le Hoang H.³^ORCID,Suganthan P. N.⁴^ORCID,Jiang Xudong⁵^ORCID,Ramasamy Savitha⁶^ORCID

Affiliation:

1. IGP-ERI@N, NTU & I2R, A*STAR, Singapore, Singapore

2. I2R, A*STAR, Singapore, Singapore

3. Ho Chi Minh University of Science, Vietnam National University, Ho Chi Minh City, Vietnam

4. Qatar University, Dohar, Qatar

5. School of Electrical and Electronic Engineering, NTU, Singapore, Singapore

6. I2R, A*STAR & CNRS@CREATE, Singapore, Singapore

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671581

Reference87 articles.

1. Ahmed Alaa, Alex James Chan, and Mihaela van der Schaar. 2021. Generative Time-series Modeling with Fourier Flows. In International Conference on Learning Representations.

2. Rahaf Aljundi Francesca Babiloni Mohamed Elhoseiny Marcus Rohrbach and Tinne Tuytelaars. 2018. Memory aware synapses: Learning what (not) to forget. In ECCV. 139--154.

3. Rahaf Aljundi Punarjay Chakravarty and Tinne Tuytelaars. 2017. Expert gate: Lifelong learning with a network of experts. In CVPR. 3366--3375.

4. Continual learning of longitudinal health records

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