This repository includes MATLAB/Python implementation of the capePCA algorithm that can achieve the same utility as the pooled-data scenario in an honest-but-curious model. Please see the original paper: https://ieeexplore.ieee.org/document/8509100
- capePCA.py -- the file contains a simple example with implementation of capePCA algorithm. It generates some synthetic data and performs the capePCA. It also computes the PCA subspaces using conventional distributed differentially-private scheme. Then it generates a plot of captured energy in the produced PCA subspace for different
$$\epsilon$$ values. - common_functions_dPCA -- MATLAB functions needed for the simulations
- datasets -- synthetic and real datasets used for the simulations
- plots -- codes for generating plots from saved results
- vs delta -- codes for variation of performance with
$$\delta$$ - vs epsilon -- codes for variation of performance with
$$\epsilon$$ - vs samples -- codes for variation of performance with number of samples
Please send bug reports, comments, or questions to Hafiz Imtiaz. Contributions and extentions with new algorithms are welcome.