Statements (57)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:software_framework
|
| gptkbp:architecture |
federated computation
|
| gptkbp:based_on |
gptkb:Tensor_Flow
|
| gptkbp:can_be_used_for |
decentralized data training
|
| gptkbp:developed_by |
gptkb:Google
|
| gptkbp:enables |
collaborative learning
|
| gptkbp:facilitates |
data privacy
|
| gptkbp:features |
simulation of federated learning
|
| gptkbp:has |
client-server architecture
community support active development |
| gptkbp:has_documentation |
available online
|
| https://www.w3.org/2000/01/rdf-schema#label |
Tensor Flow Federated
|
| gptkbp:integrates_with |
gptkb:Tensor_Flow_Model_Garden
|
| gptkbp:is |
cross-platform
flexible high-performance open-source scalable widely adopted efficient innovative modular user-friendly robust versatile community-driven well-documented collaborative decentralized extensible reliable secure actively maintained data-agnostic research-focused production-ready algorithm-agnostic model-agnostic |
| gptkbp:is_compatible_with |
gptkb:Tensor_Flow
|
| gptkbp:is_part_of |
Tensor Flow ecosystem
|
| gptkbp:license |
Apache License 2.0
|
| gptkbp:offers |
APIs for federated learning
|
| gptkbp:programming_language |
gptkb:Python
|
| gptkbp:provides |
tools for simulation
privacy-preserving machine learning secure aggregation |
| gptkbp:release_date |
gptkb:2019
|
| gptkbp:supports |
gptkb:machine_learning
custom algorithms differential privacy |
| gptkbp:used_by |
gptkb:developers
gptkb:researchers |
| gptkbp:used_for |
federated learning
|
| gptkbp:bfsParent |
gptkb:Tensor_Flow
gptkb:Federated_Learning |
| gptkbp:bfsLayer |
4
|