Low-Rank-Tensor-Completion

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Low-Rank-Tensor-Completion

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A Dual Framework for Low-rank Tensor Completion

Low-Rank-Tensor-Completion 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# A Dual Framework for Trace Norm Regularized Low-rank Tensor Completion

This package contains a MATLAB implementation of the algorithm presented in the report 
"A Dual Framework for Trace Norm Regularized Low-rank Tensor Completion" by Madhav Nimishakavi, Pratik Jawanpuria, and Bamdev Mishra; NeurIPS, 2018.

For queries and other related issues, please contact Madhav Nimishakavi (<cse.madhav@gmail.com>), Pratik Jawanpuria (<pratik.iitb@gmail.com>) or Bamdev Mishra (<bamdevm@gmail.com>).

## Installation:

1) Run run_me_first.m (needed every session).
2) Run compile_mex_c_files.m (needed to be done only once).
3) Run test_Ribeira.m. There are plots at the end.

The proposed files are under the folder 'proposed'.

## Disclaimer:

- All files are written by the authors except
    - certain initial mex files were obtained from the works of Nicolas Boumal (<nicolasboumal@gmail.com>) and (<michael.steinlechner@epfl.ch>).

- Manopt is downloaded from http://manopt.org.

## References:

Please cite the following work if you find the resources in this repository useful.

Madhav Nimishakavi, Pratik Jawanpuria, and Bamdev Mishra. <a href="https://github.com/madhavcsa/Low-Rank-Tensor-Completion/blob/master/A%20dual%20framework%20for%20low-rank%20tensor%20completion_NeurIPS18.pdf">A Dual Framework for Trace Norm Regularized Low-rank Tensor Completion</a>. In <a href="https://neurips.cc/Conferences/2018/Schedule?showEvent=11536">Conference on Neural Information Processing Systems (NeurIPS), 2018</a>.

<pre><code>@inproceedings{nimishakavi18,
  title={A Dual Framework for Trace Norm Regularized Low-rank Tensor Completion},
  author={Nimishakavi, Madhav and Jawanpuria, Pratik and Mishra, Bamdev},
  booktitle={Conference on Neural Information Processing Systems (NeurIPS)},
  year={2018}
}
</code></pre>

## License:

Low-Rank-Tensor-Completion

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