# Matrix-Completion-Methods
A simple demo for low-rank matrix completion, including the following methods:
* SVP: <br>
> [Meka, Raghu and Jain, Prateek and Dhillon, Inderjit S, "Guaranteed rank minimization via singular value projection", *arXiv preprint arXiv:0909.5457*, 2009.](https://arxiv.org/abs/0909.5457 "https://arxiv.org/abs/0909.5457")
* SVT: <br>
> [Cai, Jian-Feng and Candès, Emmanuel J and Shen, Zuowei, "A singular value thresholding algorithm for matrix completion", *SIAM Journal on optimization*, 2010.](https://epubs.siam.org/doi/abs/10.1137/080738970 "https://epubs.siam.org/doi/abs/10.1137/080738970")
* Sp-lp: <br>
> [Nie, Feiping and Wang, Hua and Cai, Xiao and Huang, Heng and Ding, Chris, "Robust matrix completion via joint schatten p-norm and lp-norm minimization", *2012 IEEE 12th International Conference on Data Mining*, 2012.](https://ieeexplore.ieee.org/abstract/document/6413869/ "https://ieeexplore.ieee.org/abstract/document/6413869/")
* TNNR-ADMM: <br>
> [Hu, Yao and Zhang, Debing and Ye, Jieping and Li, Xuelong and He, Xiaofei, "Fast and accurate matrix completion via truncated nuclear norm regularization", *IEEE transactions on pattern analysis and machine intelligence*, 2012.](https://ieeexplore.ieee.org/abstract/document/6389682/ "https://ieeexplore.ieee.org/abstract/document/6389682/")
* Sp-lp-new:
> [Nie, Feiping and Wang, Hua and Huang, Heng and Ding, Chris, "Joint Schatten p-norm and lp-norm robust matrix completion for missing value recovery", *Knowledge and Information Systems*, 2015.](https://link.springer.com/article/10.1007/s10115-013-0713-z "https://link.springer.com/article/10.1007/s10115-013-0713-z")
* ...
If you want to know more about matrix completion, please refer to this paper:
* A survey on matrix completion:
> [Li, Xiao Peng and Huang, Lei and So, Hing Cheung and Zhao, Bo, "A survey on matrix completion: Perspective of signal processing", *arXiv preprint arXiv:1901.10885*, 2019.](https://arxiv.org/pdf/1901.10885.pdf "https://arxiv.org/pdf/1901.10885.pdf")
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