CrowdFL: a marketplace for crowdsourced federated learning

• Main Authors: Feng, Daifei, Helena, Cicilia, Lim, Bryan Wei Yang, Ng, Jer Shyuan, Jiang, Hongchao, Xiong, Zehui, Kang, Jiawen, Yu, Han, Niyato, Dusit, Miao, Chunyan
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Federated Learning; Crowdsourcing
• Online Access: https://hdl.handle.net/10356/156042; https://ojs.aaai.org/index.php/AAAI/article/view/21715
• Institution: Nanyang Technological University

Amid data privacy concerns, Federated Learning (FL) has emerged as a promising machine learning paradigm that enables privacy-preserving collaborative model training. However, there exists a need for a platform that matches data owners (supply) with model requesters (demand). In this paper, we prese...