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CO-INFORMATIC GENERATIVE ADVERSARIAL NETWORKS FOR EFFICIENT DATA CO-CLUSTERING

机译:用于高效数据协同聚类的协同信息生成对抗网络

摘要

A method implemented by one or more computing systems includes accessing a first data matrix including a plurality of row data and a plurality of column data. The method further includes providing, to a first generative adversarial network (GAN), a first data input including a plurality of row vectors corresponding to the plurality of row data, and providing, to a second GAN, a second data input including a plurality of column vectors corresponding to the plurality of column data. The method further includes generating, by simultaneous co-clustering the plurality of row vectors and the plurality of column vectors by the first GAN and the second GAN, a co-clustered correlation matrix based on the plurality of row vectors and the plurality of column vectors. The method further includes the co-clustered correlation matrix includes co-clustered associations between the plurality of row data and the plurality of column data.
机译:一种由一个或多个计算系统实现的方法,包括访问包括多个行数据和多个列数据的第一数据矩阵。该方法还包括向第一生成对抗网络(GAN)提供包括与多个行数据对应的多个行向量的第一数据输入,以及向第二GAN提供包括与多个列数据对应的多个列向量的第二数据输入。该方法还包括,通过第一GAN和第二GAN同时对多个行向量和多个列向量进行共聚类,生成基于多个行向量和多个列向量的共聚类相关矩阵。该方法还包括共聚集相关矩阵,包括多个行数据和多个列数据之间的共聚集关联。

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