harlinlee/nonconvex-gtf-public

Code for nonconvex graph trend filtering

Nonconvex GTF

R. Varma*, H. Lee*, J. Kovačević and Y. Chi, “Vector-Valued Graph Trend Filtering With Non-Convex Penalties,” in IEEE Transactions on Signal and Information Processing over Networks, vol. 6, pp. 48-62, 2020.

https://ieeexplore.ieee.org/document/8926407

You can view the paper on arXiv https://arxiv.org/abs/1905.12692.

Note that when you run these scripts, numbers can be different from what is reported in the paper due to random noise.

* Figure 4 

script/support_recovery.ipynb


* Figure 5

middle panel: script(3)/script_denoising_simulation.py

right panel: script3/Runtime experiment.ipynb

datasets/2d-grid

datasets/minnesota


* Table 3

script(3)/script_diff_snr_measurements.py


* Table 4

script(3)/script_UCI_clean_data.py

script(3)/script_UCI_classification.py

script(3)/script_UCI_get_pvalues.py

datasets/UCI_data


* Figure 6

script3/NYC_taxi.ipynb


* All other figures

script/plotting.ipynb

GTF/ and scripts/ are developed in Python 2.7, and

* Numpy 1.11.3

* Scipy 1.1.0

* Pandas 0.23.4

* Matplotlib 2.2.3

* NetworkX 2.1

* Hyperopt 0.2

* PyGSP 0.5.1

GTF3/ and scripts3/ are developed in Python 3.6, and

* Numpy 1.17.0

* Scipy 1.1.0

* Pandas 0.24.2

* Matplotlib 3.0.1

* NetworkX 2.3

* Hyperopt 0.2

* PyGSP 0.5.1
	
* tqdm 4.26.0