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Federated learning is a machine learning protocol that enables a large population of agents to collaborate over multiple rounds to produce a single consensus model.
Optimal auction design
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Federated learning: Collaborative machine learning without centralized training data, Apr 2017
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Data shapley: Equitable valuation of data for machine learning
Amirata Ghorbani and James Zou · 2019
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Advances and open problems in federated learning. corr
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Incentive mechanism for reliable federated learning: A joint optimization approach to combining reputation and contract theory
Jiawen Kang, Zehui Xiong, Dusit Niyato, Shengli Xie, and Junshan Zhang · 2019
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Privacy-preserving federated brain tumour segmentation
Wenqi Li, Fausto Milletar \̀bm{i} · 2019
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Nvidia clara federated learning to deliver ai to hospitals while protecting patient data
Kimberly Powell · 2019
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A vcg-based fair incentive mechanism for federated learning
Mingshu Cong, Han Yu, Xi Weng, Jiabao Qu, Yang Liu, and Siu Ming Yiu · 2020
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Trading data for learning: Incentive mechanism for on-device federated learning
Rui Hu and Yanmin Gong · 2020
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Incentives for federated learning: a hypothesis elicitation approach
Yang Liu and Jiaheng Wei · 2020
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Budget-bounded incentives for federated learning
Adam Richardson, Aris Filos-Ratsikas, and Boi Faltings · 2020
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Federated learning for breast density classification: A real-world implementation
Holger R Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C Bizzo, et al · 2020
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Federated evaluation and tuning for on-device personalization: System design & applications
Matthias Paulik, Matt Seigel, Henry Mason, Dominic Telaar, Joris Kluivers, Rogier van Dalen, Chi Wai Lau, Luke Carlson, Filip Granqvist, Chris Vandevelde, et al · 2021
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Federated learning through revolutionary technology " consilient, Feb 2021
Gary Shiffman, Juan Zarate, Nikhil Deshpande, Raghuram Yeluri, and Parviz Peiravi · 2021
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An incentive mechanism for cross-silo federated learning: A public goods perspective
Ming Tang and Vincent WS Wong · 2021
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A contract theory based incentive mechanism for federated learning
Mengmeng Tian, Yuxin Chen, Yuan Liu, Zehui Xiong, Cyril Leung, and Chunyan Miao · 2021
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Gradient driven rewards to guarantee fairness in collaborative machine learning
Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, and Bryan Kian Hsiang Low · 2021
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Collaborative machine learning with incentive-aware model rewards
Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, and Bryan Kian Hsiang Low · 2020
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Minibatch vs local sgd for heterogeneous distributed learning
Blake E Woodworth, Kumar Kshitij Patel, and Nati Srebro · 2020
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Xinyi Xu and Lingjuan Lyu · 2020
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Fmore: An incentive scheme of multi-dimensional auction for federated learning in mec
Rongfei Zeng, Shixun Zhang, Jiaqi Wang, and Xiaowen Chu · 2020
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A learning-based incentive mechanism for federated learning
Yufeng Zhan, Peng Li, Zhihao Qu, Deze Zeng, and Song Guo · 2020
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One for one, or all for all: Equilibria and optimality of collaboration in federated learning
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, and Han Shao · 2021
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Fairfed: Enabling group fairness in federated learning
Yahya H Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, and Salman Avestimehr · 2021
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Incentive mechanism for horizontal federated learning based on reputation and reverse auction
Jingwen Zhang, Yuezhou Wu, and Rong Pan · 2021
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Fl-market: Trading private models in federated learning
Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa, Huizhong Li, and Qiang Yan · 2021
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To federate or not to federate: Incentivizing client participation in federated learning
Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, and Gauri Joshi · 2022
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Mechanisms that incentivize data sharing in federated learning
Sai Praneeth Karimireddy, Wenshuo Guo, and Michael I Jordan · 2022
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Deep federated learning for autonomous driving
Anh Nguyen, Tuong Do, Minh Tran, Binh X Nguyen, Chien Duong, Tu Phan, Erman Tjiputra, and Quang D Tran · 2022
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Fedfaim: A model performance-based fair incentive mechanism for federated learning
Zhuan Shi, Lan Zhang, Zhenyu Yao, Lingjuan Lyu, Cen Chen, Li Wang, Junhao Wang, and Xiang-Yang Li · 2022
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Enabling long-term cooperation in cross-silo federated learning: A repeated game perspective
Ning Zhang, Qian Ma, and Xu Chen · 2022
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Federated online and bandit convex optimization
Kumar Kshitij Patel, Lingxiao Wang, Aadirupa Saha, and Nathan Srebro · 2023
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