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多核谱聚类算法的有限正规化

Co-regularized Spectral Clustering with Multiple Kernels
课程网址: http://videolectures.net/nipsworkshops2010_rai_csc/  
主讲教师: Piyush Rai
开课单位: 犹他大学
开课时间: 2011-01-12
课程语种: 英语
中文简介:
我们提出了一种基于共正则化的多视图光谱聚类算法,该算法强制多个视图之间的聚类一致。由于每个视图都可以用来定义数据上的相似度图,因此我们的算法也可以被视为使用多个相似度图学习,或者等效于使用多个内核学习。我们提出了一个隐式组合两个(或更多)内核的目标函数,从而提高了集群性能。通过与多个数据集上的多个基线的实验比较,确定了我们提出的方法的有效性。
课程简介: We propose a co-regularization based multiview spectral clustering algorithm which enforces the clusterings across multiple views to agree with each-other. Since each view can be used to define a similarity graph over the data, our algorithm can also be considered as learning with multiple similarity graphs, or equivalently with multiple kernels. We propose an objective function that implicitly combines two (or more) kernels, and leads to an improved clustering performance. Experimental comparisons with a number of baselines on several datasets establish the efficacy of our proposed approach.
关 键 词: 多核谱聚类算法; 有限正则化; 目标函数
课程来源: 视频讲座网
最后编审: 2020-06-06:zyk
阅读次数: 62