| AFL | Agnostic federated learning |
| BTSB | Boosting tree secure boost |
| BYOC | Bring your own components |
| CCPA | California Consumer Privacy Act |
| CNN | Convolutional neural network |
| CP | Computing party |
| DL | Deep learning |
| DNN | Deep neural network |
| DP | Differential privacy |
| DPSGD | Differentially private stochastic gradient descent |
| FATE | Federated AI Technology Enabler |
| FedAvg | Federated averaging |
| FedMA | Federated matched averaging |
| FedProx | Federated proximal |
| FedSGD | Federated stochastic gradient descent |
| FL | Federated learning |
| FL & DP | Federated Learning and Differential Privacy |
| FLS | Federated learning system |
| GBDT | Gradient-boosting decision tree |
| GDPR | General Data Protection Regulation |
| HE | Homomorphic encryption |
| IBM FL | IBM Federated Learning |
| IID | Independent and identically distributed |
| IP | Input party |
| IoT | Internet of Things |
| IOWA | Induced ordered weighted averaging |
| LogR | Logistic regression |
| LR | Linear regression |
| LSTM | Long short-term memory |
| ML | Machine learning |
| MMARS | Medical Model ARchive |
| MPC | Multi-party computation |
| NN | Neural network |
| OWA | Ordered weighted averaging |
| PDPA | Personal data protection |
| PFF | Prefix frequency filtering |
| PFL | Paddle Federated Learning |
| PFNM | Probabilistic federated neural matching |
| PR | Poisson regression |
| PSI | Private set intersection |
| RL | Reinforcement learning |
| RNN | Recurrent neural network |
| RP | Result party |
| RPM | Revolutions per minute |
| SecAgg | Secure aggregation |
| SGD | Stochastic gradient descent |
| SPDZ | SecretShare MPC Protocol |
| TEE | Trusted execution environment |
| TF | TensorFlow |
| TFF | TensorFlow Federated |