CrowdFL: a marketplace for crowdsourced federated learning
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...
محفوظ في:
المؤلفون الرئيسيون: | Feng, Daifei, Helena, Cicilia, Lim, Bryan Wei Yang, Ng, Jer Shyuan, Jiang, Hongchao, Xiong, Zehui, Kang, Jiawen, Yu, Han, Niyato, Dusit, Miao, Chunyan |
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مؤلفون آخرون: | School of Computer Science and Engineering |
التنسيق: | Conference or Workshop Item |
اللغة: | English |
منشور في: |
2022
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الموضوعات: | |
الوصول للمادة أونلاين: | https://hdl.handle.net/10356/156042 https://ojs.aaai.org/index.php/AAAI/article/view/21715 |
الوسوم: |
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المؤسسة: | Nanyang Technological University |
اللغة: | English |
مواد مشابهة
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A marketplace for crowdsourced federated learning
بواسطة: Feng, Daifei
منشور في: (2021) -
Dynamic edge association and resource allocation in self-organizing hierarchical federated learning networks
بواسطة: Lim, Bryan Wei Yang, وآخرون
منشور في: (2022) -
CROWDFL: Privacy-preserving mobile crowdsensing system via federated learning
بواسطة: ZHAO, Bowen, وآخرون
منشور في: (2023) -
Blockchain-based privacy-preserving federated learning for mobile crowdsourcing
بواسطة: Ma, Haiying, وآخرون
منشور في: (2023) -
CrowdOp: Query Optimization for Declarative Crowdsourcing Systems
بواسطة: Fan, Ju, وآخرون
منشور في: (2020)