v1.5.0

Summary

Concrete ML v1.5 introduces several significant enhancements in this release, including a DataFrame API that enables working with encrypted stored data, a new option that speeds up neural networks by 2-3 times, an improved FHE simulation mode to quickly evaluate the impact of the speed-up on neural network accuracy.

What's Changed

Features:

• Add encrypted dataframe API (d2d6250)
• Add an option to allow approximate rounding to speed up NNs (9ef890e)
• Support ONNX conv1d operator (09ad7a6)
• Implement quantized unfold operation (fa3ef88)

Improvements:

• More accurate FHE simulation
• Encrypted aggregation of the outputs of tree ensembles
• Allow different quantization bits for tree model leaves and inputs

Fix

• Import skorch without errors due to bad docstrings (81de55c)
• Add support to AvgPool's missing parameters (15a8340)

Resources

• Documentation:
  • New structure and landing page (85cb962)
  • Add links to credit card approval space in use case examples (df81aca)
  • Improve contributing section (1696799)
  • Document n_bits for compile torch functions (0306c65)
  • Add explanation of encrypted training and federated learning (57dbdff)
  • Add documentation about scaling (9252f57)
  • Add dataframe documentation (#576) (d3bf5ac)

Links

Docker Image: zamafhe/concrete-ml:v1.5.0
Docker Hub: https://hub.docker.com/r/zamafhe/concrete-ml/tags
pip: https://pypi.org/project/concrete-ml/1.5.0
Documentation: https://docs.zama.ai/concrete-ml