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中文页面 – Dr. Yang Yang's Home Page

https://sites.temple.edu/yangyang/%E4%B8%AD%E6%96%87%E9%A1%B5%E9%9D%A2/

中文介绍 杨旸博士是美国天普大学(Temple University)体育、旅游与酒店管理学院正教授,博士生导师,系主任,同时担任美亚旅游与酒店研究中心的执行主任。作为旅游经济与分析领域的顶尖研究者,杨博士专注于旅游增长与需求建模、酒店行业的选址与财务分析以及旅游与酒店业中的大数据应用。杨 ...

Meet the Team - Temple University

https://cis.temple.edu/tagit/

We are the Temple AGI Team. We do research and experiments in the field of Artificial General Intelligence. Team meetings occur each Wednesday on Zoom. We welcome outside collaborators to get involved in various ways. Feel free to explore our various links & resources and contact us.

Resume Wizard - sites.temple.edu

https://sites.temple.edu/yangyang/files/2024/10/Yang-CV-2024-Chinese.pdf

期刊客座主编 专刊“Application of Geospatial Big Data in Tourism Research” for Applied Spatial Analysis and Policy (SSCI 索引刊物) 专刊“Technological Revolution, Digital Economy and Tourism Economics” for Tourism Economics (SSCI 索引刊物) 专刊合集“Tourism and Coronavirus” for Annals of Tourism Research (SSCI 索引刊物) 专刊“Spatial Economics and Tourism ...

ZZhao_CV_Temple

https://www.fox.temple.edu/sites/fox/files/media/document/ZZhao_CV_Temple_Sep2022_Ziyi-Zhao.pdf

University of Connecticut • MSc in Business Analytics and Project Management

Direct Care Staff Training and Competency Test

https://noncredit.temple.edu/directcarestaff

Direct Care Staff Training and Competency Test for Personal Care Homes (PCH) and Assisted Living Residences (ALR) This 6-hour online training program will give you an overview of the concepts and information needed to become a direct care staff person in a Personal Care Home (PCH) or Assisted Living Residence (ALR). This training and competency test are required before you can provide ...

Balancing Privacy and Accuracy using Significant Gradient Protection in ...

https://cis.temple.edu/~wu/research/publications/Publication_files/J-CT-2024-Balancing%20Privacy%20and%20Accuracy%20using%20Siginificant%20Gradient%20Protection%20in%20Federated%20Learning.pdf

Abstract—Previous state-of-the-art studies have demonstrated that adversaries can access sensitive user data by membership inference attacks (MIAs) in Federated Learning (FL). Intro-ducing differential privacy (DP) into the FL framework is an effective way to enhance the privacy of FL. Nevertheless, in differentially private federated learning (DP-FL), local gradients become excessively ...