Online Learning for Data Streams With Incomplete Features and Labels-Reference-Cited by-同舟云学术

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Online Learning for Data Streams With Incomplete Features and Labels

Published:2024-09 Issue:9 Volume:36 Page:4820-4834
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

You Dianlong¹^ORCID,Yan Huigui¹^ORCID,Xiao Jiawei¹^ORCID,Chen Zhen¹^ORCID,Wu Di²^ORCID,Shen Limin¹^ORCID,Wu Xindong³^ORCID

Affiliation:

1. School of Information Science and Engineering, Yanshan University, Qinhuangdao, China

2. College of Computer and Information Science, Southwest University, Chongqing, China

3. Key Laboratory of Knowledge Engineering with Big Data, Hefei University of Technology, Ministry of Education, Hefei, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

S&T Program of Hebei

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/69/10629652/10476707.pdf?arnumber=10476707

Reference51 articles.

1. Memory Efficient Class-Incremental Learning for Image Classification

2. Multi-Source Causal Feature Selection

3. Comparing the Wrapper Feature Selection Evaluators on Twitter Sentiment Classification

4. A Unified View of Causal and Non-causal Feature Selection

5. Building an efficient intrusion detection system based on feature selection and ensemble classifier

Cited by 1 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. Robust Sparse Online Learning through Adversarial Sparsity Constraints;2024 9th IEEE International Conference on Smart Cloud (SmartCloud);2024-05-10

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