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 计算数学  2018, Vol. 40 Issue (4): 354-366    DOI:
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1. 中国科学院数学与系统科学研究院, 科学与工程计算国家重点实验室, 北京 100190;
2. 中国科学院大学, 北京 100190;
3. 香港浸会大学数学系;
4. 香港理工大学应用数学系
A NEW CONTINUOUS OPTIMIZATION MODEL FOR SPECTRAL CLUSTERING
Liu Xin1,2, Michael Ng3, Zhang Rui1,2, Zhang Zaikun4
1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China;
2. University of Chinese Academy of Sciences, Beijing 100190, China;
3. Hong Kong Baptist University, China;
4. Hong Kong Polytechnic University, China
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Abstract： Clustering and graph partition play an important role in big data analysis. These problems are often formulated as combinatorial optimization models. Consequently, to solve them efficiently is difficult. In this paper, we propose a novel continuous optimization model, and a block coordinate decent method to solve it. Numerical experiments show that the new approach has great potential in dealing with clustering and graph partition problems. We also give preliminary analysis on the relationship between our model and the original combinatorial optimization model.

 引用本文: . 一种连续的谱聚类优化模型[J]. 计算数学, 2018, 40(4): 354-366. . A NEW CONTINUOUS OPTIMIZATION MODEL FOR SPECTRAL CLUSTERING[J]. Mathematica Numerica Sinica, 2018, 40(4): 354-366.

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