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Updated: Jan 7, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

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Published on: February 15, 2017

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ICIRD:基于信息原则的深度集群用于不变,冗余减少和歧视性集群分布

Aiyu Zheng1,2, Robert M X Wu3, Yupeng Wang1

  • 1School of Electronic Information and Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China.

Entropy (Basel, Switzerland)
|December 24, 2025
PubMed
概括

本研究介绍了ICIRD,这是一种新的深度集群框架,通过优化集群概率分布来增强数据分组. ICIRD减少了模糊性和冗余性,以实现更准确和不变的数据聚类.

关键词:
相反的学习学习学习.深度聚类是一种深度聚类.歧视性分布 清晰度 清晰度歧视性学习是一种歧视性的学习.基于信息原则的深度聚类.多视图集群间分布 冗余减少 多视图集群间分布

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