LibADMM Toolbox
1. Introduction
This toolbox solves many sparse, low-rank matrix and low-rank tensor optimization problems by using M-ADMM developed in our paper [1].
2. List of Problems
The table below gives the list of problems solved in our toolbox. See more details in the manual at https://canyilu.github.io/publications/2016-software-LibADMM.pdf.
3. Citation
In citing this toolbox in your papers, please use the following references:
C. Lu, J. Feng, S. Yan, Z. Lin. A Unified Alternating Direction Method of Multipliers by Majorization Minimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, pp. 527-541, 2018 C. Lu. A Library of ADMM for Sparse and Low-rank Optimization. National University of Singapore, June 2016. https://github.com/canyilu/LibADMM.
The corresponding BiBTeX citation are given below:
@manual{lu2016libadmm,
author = {Lu, Canyi},
title = {A Library of {ADMM} for Sparse and Low-rank Optimization},
organization = {National University of Singapore},
month = {June},
year = {2016},
note = {\url{https://github.com/canyilu/LibADMM}}
}
@article{lu2018unified,
author = {Lu, Canyi and Feng, Jiashi and Yan, Shuicheng and Lin, Zhouchen},
title = {A Unified Alternating Direction Method of Multipliers by Majorization Minimization},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
publisher = {IEEE},
year = {2018},
volume = {40},
number = {3},
pages = {527—-541},
}4. Version History
- Version 1.0 was released on June, 2016.
- Version 1.1 was released on June, 2018. Some key differences are below:
- Add a new model about low-rank tensor recovery from Gaussian measurements based on tensor nuclear norm and the corresponding function lrtr_Gaussian_tnn.m
- Update several functions to improve the efficiency, including prox_tnn.m, tprod.m, tran.m, tubalrank.m, and nmodeproduct.m
- Update the three example functions: example_sparse_models.m, example_low_rank_matrix_models.m, and example_low_rank_tensor_models.m
- Remove the test on image data and some unnecessary functions
References
| [1] | C. Lu, J. Feng, S. Yan, Z. Lin. A Unified Alternating Direction Method of Multipliers by Majorization Minimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, pp. 527-541, 2018 |
| [2] | C. Lu. A Library of ADMM for Sparse and Low-rank Optimization. National University of Singapore, June 2016. https://github.com/canyilu/LibADMM. |