Prof. Mingyu Xiao
Mingyu Xiao is a professor and vice dean with the School of Computer Science and Engineering, University of Electronic Science and Technology of China. He is known for his work in exact and parameterized algorithms, autonomous agents and multi-agent systems, optimization, and so on. He designed the best exact algorithms for more than 10 basic NP-hard problems, including the famous maximum independent set problem. He has authored or co-authored near 100 papers in prestigious journals and conferences, including AAAI, IJCAI, WWW, AAMAS, ICALP, I&C, JCSS and Algorithmica. He served as a conference chair/ PC chair/ area chair for FAW 2017, IJCAI 2017, NCTCS 2020 and ICCCS 2021, and a PC member for more than 20 prestigious conferences.
Score aggregation in social choice
In a score aggregation system, several agents give scores to a set of candidates independently, and we are going to combine the individual scores to get a final score for each candidate. This is a fundamental problem with a broad range of applications in social choice and many other areas. The simple and commonly used method is to sum up (or average) all scores of each candidate. In this talk, we will give good algebraic and geometric explanations for score aggregation, and introduce a new aggregation model based on the spectral method.
Some results of this talk were published on IJCAI 2017 and AAMAS 2018.