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Favorite-Candidate Voting for Eliminating the Least Popular Candidate in a Metric Space
陈旭瑾 研究员(中国科学院)
2020年8月6日 14:00-15:00  腾讯会议ID:751 890 211

*主持人:吕长虹 教授
*时间:2020年8月6日 14:00-15:00
*地点:腾讯会议ID:751 890 211

*主讲人简介:
2004年获香港大学博士学位,现为中国科学院数学与系统科学研究院研究员。主要研究兴趣和方向是组合优化的理论和应用,包括算法博弈论、网络优化、多面体组合等。2010年获“中国运筹学会青年科技奖”一等奖,2013年获首届国家优秀青年基金。

*讲座内容简介:
We study single-candidate voting embedded in a metric space, where both voters and candidates are points in the space, and the distances between voters and candidates specify the voters’ preferences over candidates. In the voting, each voter is asked to submit her favorite candidate. Given the collection of favorite candidates, a mechanism for eliminating the least popular candidate finds a committee containing all candidates but the one to be eliminated.
Each committee is associated with a social value that is the sum of the costs (utilities) it imposes (provides) to the voters. We design mechanisms for finding a committee to optimize the social value. We measure the quality of a mechanism by its distortion, defined as the worst-case ratio between the social value of the committee found by the mechanism and the optimal one. We establish new upper and lower bounds on the distortion of mechanisms in this single-candidate voting, for both general metrics and well-motivated special cases. (Joint work with Minming Li and Chenhao Wang.)