Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. Scaling laws for neural language models. CoRR, abs/2001.08361, 2020. URL https://arxiv.org/abs/2001.08361.
Sai Praneeth Karimireddy, Wenshuo Guo, and Michael Jordan. Mechanisms that incentivize data sharing in federated learning. In Workshop on Federated Learning: Recent Advances and New Challenges (in Conjunction with NeurIPS 2022), 2022. URL https://openreview.net/forum? id=Bx4Sz-N5K3J.
Alex Krizhevsky. Learning multiple layers of features from tiny images. Technical Report TR-2009, University of Toronto, Toronto, 2009. URL https://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf.
Kenneth C Laudon. Markets and privacy. Communications of the ACM, 39(9):92-104, 1996.
Federated Learning. Collaborative machine learning without centralized training data. Publication date: Thursday, April, 6, 2017.
Yann LeCun, Corinna Cortes, and CJ Burges. MNIST handwritten digit database. ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist, 2, 2010.
Tian Li, Maziar Sanjabi, Ahmad Beirami, and Virginia Smith. Fair resource allocation in federated learning. In ICLR. OpenReview.net, 2020.
Xiao-Bai Li and Srinivasan Raghunathan. Pricing and disseminating customer data with privacy awareness. Decision support systems, 59:63-73, 2014.
H. Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Agüera y Arcas. Communication-efficient learning of deep networks from decentralized data. In International Conference on Artificial Intelligence and Statistics (AISTATS), 2017.
M. Mohri, A. Rostamizadeh, and A. Talwalkar. Foundations of Machine Learning, second edition. Adaptive Computation and Machine Learning series. MIT Press, 2018. ISBN 9780262039406. URL https://books.google.com/books?id=V2B9DwAAQBAJ.
Mehryar Mohri, Gary Sivek, and Ananda Theertha Suresh. Agnostic federated learning. In International Conference on Machine Learning, pages 4615-4625. PMLR, 2019.
Hervé Moulin. *Fair Division and Collective Welfare*. The MIT Press, 01 2003. ISBN 9780262280297. doi: 10.7551/mitpress/2954.001.0001. URL https://doi.org/10.7551/mitpress/2954.001.0001.
Roger B Myerson. Optimal auction design. Mathematics of operations research, 6(1):58-73, 1981.
John Nash. Non-cooperative games. Ann. Math., 54(2):286-295, 1951.
N Nvidia. Nvidia clara federated learning to deliver ai to hospitals while protecting patient data. NVIDIA Clara Federated Learning to Deliver AI to Hospitals While Protecting Patient Data, 2019.
J. B. Rosen. Existence and uniqueness of equilibrium points for concave n-person games. *Economometrica*, 33(3):520-534, 1965. ISSN 00129682, 14680262. URL http://www.jstor.org/stable/1911749.
Paul A. Samuelson. The pure theory of public expenditure. The Review of Economics and Statistics, 36(4):387-389, 1954. ISSN 00346535, 15309142. URL http://www.jstor.org/stable/1925895.
Karen Simonyan and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556, 2014.
Hal R Varian. Equity, envy, and efficiency. Journal of Economic Theory, 9(1):63 - 91, 1974.
Jie Xu, Benjamin S Glicksberg, Chang Su, Peter Walker, Jiang Bian, and Fei Wang. Federated learning for healthcare informatics. Journal of Healthcare Informatics Research, 5(1):1-19, 2021.