Semi-supervised Drifted Stream Learning with Short Lookback-Reference-Cited by-同舟云学术

Semi-supervised Drifted Stream Learning with Short Lookback

Published:2022-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Ren Weijieying¹,Wang Pengyang²,Li Xiaolin³,Hughes Charles E.¹,Fu Yanjie¹

Affiliation:

1. University of Central Florida, Orlando, FL, USA

2. University of Macau, Macau, China

3. Nanjing University, Nanjing, China

Funder

National Science Foundation

U.S. Department of Education

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539297

Reference27 articles.

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2. Aristotelis Chrysakis and Marie-Francine Moens . 2020 . Online continual learning from imbalanced data . In International Conference on Machine Learning. PMLR. Aristotelis Chrysakis and Marie-Francine Moens. 2020. Online continual learning from imbalanced data. In International Conference on Machine Learning. PMLR.

3. Danruo Deng , Guangyong Chen , Jianye Hao , Qiong Wang , and Pheng-Ann Heng . 2021 . Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning . Advances in Neural Information Processing Systems , Vol. 34 (2021). Danruo Deng, Guangyong Chen, Jianye Hao, Qiong Wang, and Pheng-Ann Heng. 2021. Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning. Advances in Neural Information Processing Systems, Vol. 34 (2021).

4. Unsupervised Visual Domain Adaptation Using Subspace Alignment

5. RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift

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