可扩展结构化低秩矩阵优化问题Scalable Structured Low Rank Matrix Optimization Problems |
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课程网址: | http://videolectures.net/roks2013_signoretto_optimization/ |
主讲教师: | Marco Signoretto |
开课单位: | 鲁汶大学 |
开课时间: | 2013-08-26 |
课程语种: | 英语 |
中文简介: | 我们考虑一类结构化的低秩矩阵优化问题。我们通过线性映射(称为突变)表示所需的结构,该线性映射可以编码矩阵,其中矩阵的条目划分为已知的不连续的组。我们的兴趣尤其来自串联块Hankel矩阵,这些矩阵出现在具有噪声和/或部分未观测数据的输入输出线性系统识别问题的公式中。我们提出一种算法,并针对现有的替代方法进行测试。 p> |
课程简介: | We consider a class of structured low rank matrix optimization problems. We represent the desired structure by a linear map, termed mutation, that can encode matrices having entries partitioned into known disjoined groups. Our interest arises in particular from concatenated block-Hankel matrices that appear in formulations for input-output linear system identification problems with noisy and/or partially unobserved data. We present an algorithm and test it against an existing alternative. |
关 键 词: | 矩阵; 线性系统 |
课程来源: | 视频讲座网 |
数据采集: | 2021-01-06:zyk |
最后编审: | 2021-01-06:zyk |
阅读次数: | 85 |