L0 Regularization

L0 is a PyTorch implementation of L0 regularization for neural network sparsification and intelligent sampling, used in PolicyEngine's survey calibration pipeline.

For Users

What is L0?

L0 regularization helps PolicyEngine create more efficient survey datasets by intelligently selecting which households to include in calculations.

Impact you see:

• Faster population impact calculations
• Smaller dataset sizes
• Maintained accuracy with fewer samples

Behind the scenes: When PolicyEngine shows population-wide impacts, L0 helps select representative households from the full survey, reducing computation time while maintaining accuracy.

For Analysts