This Python package provides efficient implementations of algorithms for sparse Principal Component Analysis (PCA), as proposed in our research paper. The algorithm is designed for fast computation and improved sample complexity.
If you use this code or algorithm in your research, please cite:
Jian-Feng Cai, Zhuozhi Xian, and Jiaxi Ying, Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity, International Conference on Machine Learning (ICML), 2025.
To run the code:
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Download or clone the source files.
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Ensure you have Python 3 installed.
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Run the demonstration script:
python demo.py