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子空间聚类的重建模型及其快速算法

本站小编 Free考研考试/2021-12-27

夏雨晴1, 张振跃2
1. 浙江大学 数学科学学院, 杭州 310027;
2. 浙江大学 数学科学学院;CAD&CG国家重点实验室, 杭州 310027
收稿日期:2018-09-26出版日期:2019-03-15发布日期:2019-02-18


基金资助:国家自然科学基金(11571312,91730303)和中国国家重点基础研究发展计划(2015CB352503)资助项目.


RECONSTRUCTION MODEL AND FAST ALGORITHM FOR SUBSPACE CLUSTERING

Xia Yuqing1, Zhang Zhenyue2
1. School of Mathematics Science, Zhejiang University, 310027 Hangzhou, China;
2. School of Mathematics Science and State Key Laboratory of CAD & CG, 310027 Hangzhou, China
Received:2018-09-26Online:2019-03-15Published:2019-02-18







摘要



编辑推荐
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有限样本的子空间数据聚类建模及其大规模计算是子空间学习面临的主要问题.现有的大多数模型都不适合大规模计算.本文提出了一个新的优化模型,结合谱投影反馈和辅助信息优化.在提升模型的学习能力的同时,采用高效的分片符号更新算法,可以适合大规模计算.我们用较大规模的模拟例子和实际例子,分析检验了新的优化模型及其快速算法的优于现有其他模型与算法的有效性.
MR(2010)主题分类:
58C40
62H30
74P99

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