Privacy-preserving distributed projection LMS for linear multitask networks

• المؤلفون الرئيسيون: Wang, Chengcheng, Tay, Wee Peng, Wei, Ye, Wang, Yuan
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Computer science and engineering; Engineering::Electrical and electronic engineering::Electronic systems::Signal processing; Distributed Strategies; Multitask Networks; Inference Privacy; Privacy Preservation; Additive Noises
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/156347
• المؤسسة: Nanyang Technological University

We develop a privacy-preserving distributed projection least mean squares (LMS) strategy over linear multitask networks, where agents' local parameters of interest or tasks are linearly related. Each agent is interested in not only improving its local inference performance via in-network cooper...