Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications
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Cited by:
- Vivek Kumar Prasad & Pronaya Bhattacharya & Darshil Maru & Sudeep Tanwar & Ashwin Verma & Arunendra Singh & Amod Kumar Tiwari & Ravi Sharma & Ahmed Alkhayyat & Florin-Emilian Čšurcanu & Maria Simona Ra, 2022. "Federated Learning for the Internet-of-Medical-Things: A Survey," Mathematics, MDPI, vol. 11(1), pages 1-47, December.
- Longbing Cao, 2021. "AI in Finance: Challenges, Techniques and Opportunities," Papers 2107.09051, arXiv.org.
- Xiao-Yang Liu & Guoxuan Wang & Hongyang Yang & Daochen Zha, 2023. "FinGPT: Democratizing Internet-scale Data for Financial Large Language Models," Papers 2307.10485, arXiv.org, revised Nov 2023.
- Xiao-Yang Liu & Ziyi Xia & Jingyang Rui & Jiechao Gao & Hongyang Yang & Ming Zhu & Christina Dan Wang & Zhaoran Wang & Jian Guo, 2022. "FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning," Papers 2211.03107, arXiv.org.
- David Cerezo S'anchez, 2021. "JUBILEE: Secure Debt Relief and Forgiveness," Papers 2109.07267, arXiv.org.
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This paper has been announced in the following NEP Reports:- NEP-CMP-2020-11-09 (Computational Economics)
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