报告题目: Privacy Issues in Recommender Systems

报告人：Qiang Tang（Senior Researcher）

主持人：曹珍富（教授）

报告时间：10月16日（周一）10:30-12:00

报告地点：中北校区数学馆201室

报告摘要:

       A recommender system predicts the preferences that users would give to an item, so that it enables users to make the most appropriate choices from the immense variety of items that are available. When recommender systems continue to penetrate into our life and extract every detail possible, more and more concerns have emerged. Worries against such systems root in their greedy demand for personal data, the strong economic or even political incentives behind players, and the ever-increasing system complexity of the underlying algorithms that can (un)intentionally result in discrimination and fairness problems. At this moment, actions are desperately needed to tackle a wide range of issues in such systems. In this talk, we will survey some existing privacy-preserving recommender solutions and try to shed some light on the entanglement of privacy, robustness, and transparency.

报告人简介:

      Dr Qiang Tang is a Senior Researcher at Luxembourg Institute of Science and Technology (LIST), which is a newly established research center in Luxembourg. The goal of his research is to bridge the gap between theoretical cryptographic, security and privacy technologies and the practical needs in real-world cloud computing, big data, Fintech, IoT applications. He is interested in investigating the requirements from the underlying scenarios, formulating them into rigorous properties in the theoretical primitives, and searching for efficient solutions. In his research, he often takes a data-driven research methodology, aiming at understanding the comprehensive implications of data handling in target applications.