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System and method for structured low-rank matrix factorization: optimality, algorithm, and applications to image processing
System and method for structured low-rank matrix factorization: optimality, algorithm, and applications to image processing
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机译:结构化低秩矩阵分解的系统和方法:最优性,算法及其在图像处理中的应用
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摘要
The present invention provides a system and method for structured low-rank matrix factorization of data. The system and method involve solving an optimization problem that is not convex, but theoretical results should that a rank-deficient local minimum gives a global minimum. The system and method also involve an optimization strategy that is highly parallelizable and can be performed using a highly reduced set of variables. The present invention can be used for many large scale problems, with examples in biomedical video segmentation and hyperspectral compressed recovery.
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