Release 1.0
Major Features and Improvements
This version includes two new products of FATE, FATE-Board, and FATE-Flow respectively, FATE-Board as a visual tool for federation modeling, and FATE-Flow is an end to end pipeline platform for federated learning. This version contains important improvements to the FederatedML, which better tracks the running progress of federated learning algorithms.
FATE-Board
- Federated Learning Job DashBoard
- Federated Learning Job Visualisation
- Federated Learning Job Management
- Real-time Log Panel
FATE-FLOW
- DAG defines Pipeline
- Federated Multi-party asymmetric DSL parser
- Federated Learning lifecycle management
- Federated Task collaborative scheduling
- Tracking for data, metric, model and so on
- Federated Multi-party model management
FederatedML
- Update all algorithm modules running mechanism for supporting federated modeling pipeline by FATE-Flow
- Intermediate statistic result callback is available and visualizable in FATE-Board for all algorithm modules.
- Support Nesterov Momentum SGD Optimizer
- Add Homomorphic Encryption Scheme Based on Affine Transforms
- Support sparse input-format in federated feature binning
- Update evaluation metrics, such as ks, roc, gain, lift curve and so on
- Update algorithm's parameter-define class
FATE-Serving
- Add online federated modeling pipeline DSL parser for online federated inference