Semi-supervised federated heterogeneous transfer learning

• المؤلفون الرئيسيون: Feng, Siwei, Li, Boyang, Yu, Han, Liu, Yang, Yang, Qiang
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Computer science and engineering; Federated Transfer Learning; Data Privacy Preservation
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/163377
• المؤسسة: Nanyang Technological University

Federated learning (FL) is a privacy-preserving paradigm that collaboratively train machine learning models with distributed data stored in different silos without exposing sensitive information. Different from most existing FL approaches requiring data from different parties share either the same f...