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 ℓp-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}
}
-
Matlab
-
MNIST Dataset MNIST data files File format as specified on http://yann.lecun.com/exdb/mnist/
Run the Matlab files in the "Synthetic data" folder
Run the Matlab files in the "lp-mnist" folder
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}}