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个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职：人力资源处处长（党委教师工作部部长、党委人才办公室主任）【兼党委组织部副部长】
性别：男
毕业院校：上海交通大学
学位：博士
所在单位：生物医学工程学院
学科：生物医学工程. 信号与信息处理. 模式识别与智能系统
电子邮箱：cong@dlut.edu.cn
FAST IMPLEMENTATION OF DOUBLE-COUPLED NONNEGATIVE CANONICAL POLYADIC DECOMPOSITION
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论文类型：会议论文
发表时间：2019-01-01
收录刊物：EI、CPCI-S
卷号：2019-May
页面范围：8588-8592
关键字：Tensor decomposition; coupled tensor decomposition; Hierarchical Alternating Least Squares (HALS); linked CP tensor decomposition (LCPTD)
摘要：Real-world data exhibiting high order/dimensionality and various couplings are linked to each other since they share some common characteristics. Coupled tensor decomposition has become a popular technique for group analysis in recent years, especially for simultaneous analysis of multi-block tensor data with common information. To address the multiblock tensor data, we propose a fast double-coupled non-negative Canonical Polyadic Decomposition (FDC-NCPD) algorithm in this study, based on the linked CP tensor decomposition (LCPTD) model and fast Hierarchical Alternating Least Squares (Fast-HALS) algorithm. The proposed FDC-NCPD algorithm enables simultaneous extraction of common components, individual components and core tensors from tensor blocks. Moreover, time consumption is greatly reduced without compromising the decomposition quality when handling large-scale tensor blocks. Simulation experiments of synthetic and real-world data are conducted to demonstrate the superior performance of the proposed algorithm.