MarS-FL: enabling competitors to collaborate in federated learning

• Main Authors: Wu, Xiaohu, Yu, Han
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Federated learning; Competitive Market
• Online Access: https://hdl.handle.net/10356/164431
• Institution: Nanyang Technological University

Federated learning (FL) is rapidly gaining popularity and enables multiple data owners (a.k.a. FL participants) to collaboratively train machine learning models in a privacy-preserving way. A key unaddressed scenario is that these FL participants are in a competitive market, where market shares repr...