Federated Learning with Local Differential Privacy
What it is
A PyTorch-based framework for implementing federated learning with local differential privacy (LDP). It provides a mechanism to train multiple types of neural networks and SVMs while ensuring individual data privacy.
The problem it solves
The challenge of training shared models on distributed data without exposing raw user information or private data points.
What you could use it for
- Training CNNs on distributed datasets while preserving user privacy
- Implementing MLP models with LDP in a federated learning environment
- Privacy-preserving machine learning on the Adult dataset
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Summary written by an AI model from the source; check the source before you rely on it.