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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/136871


    Title: 聯邦學習:在智能金融上的應用
    Authors: 劉啟東
    Contributors: 謝明華
    劉啟東
    Keywords: 聯邦
    智能金融
    Date: 2021
    Issue Date: 2021-09-02 16:08:35 (UTC+8)
    Abstract: 本研究介紹了聯邦式學習的興起原因和目前的應用,從聯邦學習的概念和分類,解釋了其與傳統機器學習不同的地方。它打破了數據壁壘,使得客戶可以在本地進行訓練模型,而不會洩露資料的隱私。同時也討論了目前應用較為廣泛的聯邦式學習框架。通過個案的分析,討論了目前聯邦學習在金融領域的應用,通過聯邦技術計算保費,幫助小型銀行預測客戶的信用,進行金融犯罪行,再開放銀行的應用和未來聯邦式學習可以和區塊鏈技術相結合,從而能夠幫助聯邦式學習處理目前難以處理的難點。
    Reference: 中文部分:

    1. 王春凱,馮鍵 (2020). "聯邦學習在保險行業的研究應用." 保險職業學院學報 第34 期: 13-17.
    2. 周俊, et al. (2020). "聯邦學習安全与隱私保護研究綜述." 西華大學學報 (自然科學版) 39(4): 9-17.
    3. 於建科 (2017). 反欺詐行業深度報告之一——金融反詐欺行業發展前景良好. 新三板-行業專題報告, 方正證券.
    4. 邱鑫源, et al. (2021). "聯邦學習通信开销研究綜述." 计算机應用: 0-0.
    5. 麥肯錫 (2019). 開放銀行的全球實踐與展望.
    6. 微眾銀行人工智能部, et al. (2020). "聯邦學習白皮書 V2.0." from https://ai.webankcdn.net/scvm/html/1586314655296.html.
    7. 譚樂之 (2019). "微眾銀行與瑞士再保險簽署合作備忘錄." from http://xw.sinoins.com/2019-05/22/content_292101.htm.
    8. 蘇建明, et al. (2020). "聯邦學習在商業銀行反欺詐領域的應用." 中國金融電腦:39-42.
    9. FedAI. "聯邦學習應用案例." from https://cn.fedai.org/cases.
    10. 監督式學習與非監督式學習的差異、應用以及案例(2020)." from https://oosga.com/thinking/difference-between-supervised-learning-and-unsupervised-learning.
    11. 何寶宏,覃敏.大數據須結束數據孤島[J].新世紀周刊,2013,(33):70-72.


    英文部分:

    1. Duan, M., et al. (2020). "Self-balancing federated learning with global imbalanced data in mobile systems." IEEE Transactions on Parallel and Distributed Systems 32(1): 59-71.
    2. FinRegLab (2020). Federated Machine Learning in Anti-Financial Crime Processes, FinRegLab: 1-14.
    3. Long, G., et al. (2020). Federated Learning for Open Banking. Federated Learning, Springer: 240-254.
    4. Ryffel, T., et al. (2018). "A generic framework for privacy preserving deep learning." arXiv preprint arXiv:1811.04017.
    5. Truex, S., et al. (2019). A hybrid approach to privacy-preserving federated
    learning. Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security.
    6. Yang, Q., et al. (2019). "Federated machine learning: Concept and applications." ACM Transactions on Intelligent Systems and Technology (TIST) 10(2): 1-19.
    7. Wüst, K., & Gervais, A. (2018, June). Do you need a blockchain?. In 2018 Crypto Valley Conference on Blockchain Technology (CVCBT) (pp. 45-54). IEEE.
    8. Gupta, S. S. (2017). Blockchain. IBM Onlone (http://www. IBM. COM).
    Description: 碩士
    國立政治大學
    經營管理碩士學程(EMBA)
    104932418
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0104932418
    Data Type: thesis
    DOI: 10.6814/NCCU202101271
    Appears in Collections:[經營管理碩士學程EMBA] 學位論文

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