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Updated: Sep 18, 2025

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作为的原型:解决在线持续学习的未见噪音问题

Shao-Yuan Li1, Yu-Xiang Zheng2, Sheng-Jun Huang2

  • 1MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; State Key Lab. for Novel Software Technology, Nanjing University, Nanjing, 211106, PR China; Joint Laboratory of Spatial Intelligent Perception and Large Model Application, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, PR China.

Neural networks : the official journal of the International Neural Network Society
|June 22, 2025
PubMed
概括

本研究介绍了原型作为 (PAA),这是一种在线课程增量持续学习 (CIL) 的新方法,可以有效地处理噪音标签和未知的课程. 在动态环境中,PAA显著提高了模型性能和稳定性.

关键词:
持续的学习 持续的学习噪音标签 噪音标签 噪音标签开放式设置的噪声.

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