Comments (2)
Hello,
Thank you very much for your interest in Concrete-ML !
For the moment, Concrete ML is mainly focusing in protecting the inferences' privacy and we unfortunately don't handle model training with homomorphically encrypted data. However, this may change in the future, but currently this is not Zama's first priority and we are just not able to say when would that be available.
In fact, our current FHE constraints would make this training quite a challenge, considering the fact that we use 8 bits of precision, while making the running time particularly slow. In order to handle training on encrypted data, you may have a look into other more adapted technologies than FHE (differential privacy, multi party computation) until we offer that feature in Concrete-ML.
I hope this answers your question !
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Hello Roman,
Thank you for the quick reply and the info. I will take a look at other options that you suggested, and see how they might combine with what you already have.
Have a nice day!
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Related Issues (20)
- Feature Request : Implement LogSoftmax, Softmax, ReduceMax HOT 3
- Performance Issues HOT 1
- Two consecutive Unsqueeze operations in QAT model throws error at compilation time HOT 2
- LLVM symbolizer error with LogisticRegression example HOT 15
- [Question] What HE algorithm is used? HOT 6
- [Question] AssertionError: Values must be float if value_is_float is set to True, got int64: [1] HOT 3
- AssertionError: Values must be float if value_is_float is set to True, got int64: [[[[102 14 188 ... 85 205 46] HOT 3
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! HOT 7
- Python 3.12 HOT 2
- Adding encrypted training for other ML models and DL models HOT 5
- quantized_module.forward() occured an error in "execute" mode HOT 8
- Feature request: Support Unfold torch operator HOT 10
- LLVM symbolizer error when running FHE in 'execute' mode HOT 7
- [Question] How does ReLU work in the new NN example HOT 6
- Feature request: support more padding method HOT 1
- Accuracy of XGBClassifier of disable mode HOT 2
- GPU acceleration in concrete-ml ? HOT 3
- Making a fast satellite image classification use case [was: Some questions about GPU acceleration] HOT 24
- [Public issue] AssertionError assert repr_input_shape in self.clients in hybrid model with multiple submodules HOT 7
- [Feature Request] Support for threshold decryption HOT 1
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