Differential Privacy Stochastic Gradient Descent

1. Split training data into mini batches
2. Find which samples best modify weight
3. Gradient Clipping
4. Average the gradients to reflect all changes
5. Add Noise corresponding to size of mini batch Usually patterns emerge from shared characteristics between people, so DP works