Research Area:  Machine Learning

Abstract:

Despite its great progress so far, artificial intelligence (AI) is facing a serious challenge in the availability of high-quality Big Data. In many practical applications, data are in the form of isolated islands. Efforts to integrate the data are increasingly difficult partly due to serious concerns over user privacy and data security. The problem is exacerbated by strict government regulations such as Europes General Data Privacy Regulations (GDPR). In this talk, I will review these challenges and describe efforts to address them in recommendation systems area. In particular, I will give an overview of recent advances in federated learning and then focus on developments of “federated recommendation systems”, which aims to build high-performance recommendation systems by bridging data repositories without compromising data security and privacy.

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Author(s) Name:  Yang Qiang

Publisher name:  IEEE

DOI:  10.1109/BigData47090.2019.9005952

Volume Information:  

Paper Link:   https://ieeexplore.ieee.org/abstract/document/9005952