LpDL

This is an open-source implementation for our series work on dictionary learning.

The primary work is the UAI 2020 submission "Complete Dictionary Learning via ℓ_p-norm Maximization'', Yifei Shen∗, Ye Xue∗, Jun Zhang, Khaled B. Letaief, Vincent Lau. [pdf]

The main theoretical results are summarized in this work. If you find they are useful, please cite:

@InProceedings{pmlr-v124-shen20a,
  title = 	 {Complete Dictionary Learning via $\ell_p$-norm Maximization},
  author =       {Shen, Yifei and Xue, Ye and Zhang, Jun and Letaief, Khaled and Lau, Vincent},
  pages = 	 {280--289},
  year = 	 {2020},
  editor = 	 {Jonas Peters and David Sontag},
  volume = 	 {124},
  series = 	 {Proceedings of Machine Learning Research},
  address = 	 {Virtual},
  month = 	 {03--06 Aug},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v124/shen20a/shen20a.pdf},
  url = 	 {http://proceedings.mlr.press/v124/shen20a.html}
}

1.0 Prerequisites

• Matlab

• MNIST Dataset MNIST data files File format as specified on http://yann.lecun.com/exdb/mnist/

2.0 Run the experiment for synthetic data

Run the Matlab files in the "Synthetic data" folder

3.0 Run the experiment for MNIST data

Run the Matlab files in the "lp-mnist" folder

4.0 Application for Blind Data Detection

Run the code in the "L3_BlindDataDetection" folder, which provides the elementary code for algorithmic verification for the paper "Blind Data Detection in Massive MIMO via ℓ3-norm Maximization over the Stiefel Manifold," Y. Xue, Y. Shen, V. Lau, J. Zhang and K. B. Letaief, in IEEE Transactions on Wireless Communications.[pdf] If you find this application is helpful, please cite

@ARTICLE{9246702,
  author={Y. {Xue} and Y. {Shen} and V. {Lau} and J. {Zhang} and K. B. {Letaief}},
  journal={IEEE Transactions on Wireless Communications}, 
  title={Blind Data Detection in Massive MIMO via ℓ3-norm Maximization over the Stiefel Manifold}, 
  year={2020},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TWC.2020.3033699}}