报告题目：Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations

报告人：Amo Tong, University of Delaware

报告时间：2023年3月16日（星期四）9:00-10:00

报考方式：腾讯会议室：744-8325-9832

报告摘要：Considering two decision-making tasks A and B each of which wishes to compute an effective decision for a given query, can we solve task A by using query-decision pairs of B without knowing the latent decision-making model? Such problems, called inverse decision-making with task migrations, are of interest in that the complex and stochastic nature of real-world applications often prevents the agent from completely knowing the underlying system. In this paper, we introduce such a new problem with formal formulations and present a generic framework for addressing decision-making tasks in social contagion management. On the theory side, we present a generalization analysis for justifying the learning performance of our framework. In empirical studies, we perform a sanity check and compare the presented method with other possible learning-based and graph-based methods. We have acquired promising experimental results, confirming for the first time that it is possible to solve one decision-making task by using the solutions associated with another one.（该工作发表于NeurIPS2022）

报告人简介：Dr. Guangmo Tong is an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware. He received a Ph.D. in Computer Science from the University of Texas at Dallas, and a BS degree in Mathematics and Applied Mathematics from Beijing Institute of Technology. His research interests include combinatorial optimization, machine learning, and computational social systems.