Code for replicating the experiments in the paper Kernel Feature Selection via Conditional Covariance Minimization by Jianbo Chen*, Mitchell Stern*, Martin J. Wainwright, Michael I. Jordan. (* indicates equal contribution)

The code for CCM runs with Python and requires Tensorflow of version 1.2.1 or higher. Please pip install the following packages:

• numpy
• tensorflow

Or you may run the following and in shell to install the required packages:

git clone https://github.com/Jianbo-Lab/CCM
cd CCM
sudo pip install -r requirements.txt

We provide as an example the source code to run CCM on the three synthetic datasets in the paper. Run the following commands in shell:

###############################################
# Omit if already git cloned.
git clone https://github.com/Jianbo-Lab/CCM
cd CCM 
############################################### 
python examples/run_synthetic.py

See core/ccm.py and examples/run_synthetic.py for details.

If you use this code for your research, please cite our paper:

@incollection{NIPS2017_7270,
title = {Kernel Feature Selection via Conditional Covariance Minimization},
author = {Chen, Jianbo and Stern, Mitchell and Wainwright, Martin J and Jordan, Michael I},
booktitle = {Advances in Neural Information Processing Systems 30},
editor = {I. Guyon and U. V. Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
pages = {6949--6958},
year = {2017},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/7270-kernel-feature-selection-via-conditional-covariance-minimization.pdf}
}