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Spark-Based Large-Scale Matrix Inversion for Big Data Processing
2016
IEEE Access
Matrix inversion is a fundamental operation for solving linear equations for many computational applications, especially for various emerging big data applications. However, it is a challenging task to invert large-scale matrices of extremely high order (several thousands or millions), which are common in most web-scale systems such as social networks and recommendation systems. In this paper, we present a LU decomposition-based block-recursive algorithm for large-scale matrix inversion. We
doi:10.1109/access.2016.2546544
fatcat:npwy2xc4y5dqlbji2o4g2wniye