/ASCCA

Trace Lasso Regularization for Adaptive Sparse Canonical Correlation Analysis via Manifold Optimization Approach

Primary LanguageMATLABMIT LicenseMIT

Our code is based on "manopt toolbox" and code in paper "An inexact augmented Lagrangian method for nonsmooth optimization on Riemannian manifold"

ASCCA is a adaptive sparse CCA model by incorporating the matrix trace Lasso regularization

References

If you use these codes in an academic paper, please cite the following papers.

Kangkang, Deng, and Peng Zheng, An Inexact Manifold Augmented Lagrangian Method for Adaptive Sparse Canonical Correlation Analysis with Trace Lasso Regularization, arXiv preprint arXiv:2003.09195 (2020).

Authors

To Contact Us

If you have any questions or find any bugs, please feel free to contact us by email (dengkangkang@pku.edu.cn).

License

You can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

MIALM is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Please see the GNU Lesser General Public License for more details.