BlockFL: blockchain-enabled decentralized federated learning and model trading
Federated Learning (FL) is a promising privacy-preserving distributed machine learning paradigm. However, there is only a centralized parameter server to aggregate all the local model updates, which brings the challenges of a single point of failure and server overload, especially in large-scale tra...
Saved in:
Main Author: | Pham, Tan Anh Khoa |
---|---|
Other Authors: | Dusit Niyato |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/156495 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Auditable and verifiable federated learning based on blockchain-enabled decentralization
by: Kalapaaking, Aditya Pribadi, et al.
Published: (2024) -
MarS-FL: enabling competitors to collaborate in federated learning
by: Wu, Xiaohu, et al.
Published: (2023) -
Blockchain-enabled federated learning with mechanism design
by: Toyoda, Kentaroh, et al.
Published: (2021) -
Decentralized federated learning
by: Hitesh, Agarwal
Published: (2022) -
CrowdFL: a marketplace for crowdsourced federated learning
by: Feng, Daifei, et al.
Published: (2022)