Boosting privately: Federated extreme gradient boosting for mobile crowdsensing

• المؤلفون الرئيسيون: LIU, Yang, MA, Zhuo, LIU, Ximeng, MA, Siqi, NEPAL, Surya, DENG, Robert H., REN, Kui
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2020
• الموضوعات: Privacy-Preserving; Federated learning; Extreme gradient boosting; Mobile crowdsensing; Information Security
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/5921; https://ink.library.smu.edu.sg/context/sis_research/article/6924/viewcontent/BoostingPrivately_av.pdf

Recently, Google and other 24 institutions proposed a series of open challenges towards federated learning (FL), which include application expansion and homomorphic encryption (HE). The former aims to expand the applicable machine learning models of FL. The latter focuses on who holds the secret key...