yingcuhk / RLRA

Convex-Restricted Low-Rank Matrix Approximation (CLA)

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RLRA-OPF

This package tries to solve the matrix low-rank approximation problem by alternating direction methods of multipliers. This problem can find its position in many applications. Specifically, we try to recover a feasible solution for the optimal power flow problem when the SDP (semidefinite programming) relaxation is inexact.

The tech report can be found in http://arxiv.org/abs/1512.01748

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Convex-Restricted Low-Rank Matrix Approximation (CLA)


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