dp sgd

Privacy is a governance requirement that becomes a training-time technique. The signal is knowing what differential privacy actually guarantees (and its cost), and how federated learning and DP combine. Here is the rigorous, honest answer.

Epsilon is the privacy knob, and shipping DP means choosing a number, defending it, and tracking what each query spends. The signal is treating epsilon as a finite budget with composition, not a magic constant. Here is the answer.