The ELLIS PhD program is a European initiative that supports excellent young researchers by connecting them to leading researchers in AI. In particular, PhD students are supervised by two advisors from different countries: an advisor and a co-advisor. In this work we summarize the procedure that, in its final step, matches students to advisors in the ELLIS 2020 PhD program. The steps of the procedure are based on the extensive literature of two-sided matching markets and the college admissions problem [Knuth and De Bruijn, 1997, Gale and Shapley, 1962, Rothand Sotomayor, 1992]. We introduce PolyGS, an algorithm for the case of two-sided markets with quotas on both sides (also known as many-to-many markets) which we use throughout the selection procedure of pre-screening, interview matching and final matching with advisors. The algorithm returns a stable matching in the sense that no unmatched persons prefer to be matched together rather than with their current partners (given their indicated preferences). Roth [1984] gives evidence that only stable matchings are likely to be adhered to over time. Additionally, the matching is student-optimal. Preferences are constructed based on the rankings each side gives to the other side and the overlaps of research fields. We present and discuss the matchings that the algorithm produces in the ELLIS 2020 PhD program.
翻译:ELLIS博士方案是一个欧洲倡议,它通过将优秀的年轻研究人员与AI的主要研究人员联系起来来支持优秀的年轻研究人员。特别是,博士生由来自不同国家的两位顾问监督:一位顾问和一位共同顾问。在这项工作中,我们总结了在最后一步将学生与ELLIS2020博士方案顾问相匹配的程序。程序的步骤基于双向匹配市场的广泛文献以及大学录取问题[Knuth和De Bruijn,1997年,Gale和Shapley,1962年,Rothand Sotomayor,1992年]。我们引入了PolyGS,这是两面制配额的双面市场(也称为多对多对多市场)的算法。我们在整个甄选程序中都使用了预先筛选、面试和与顾问最后匹配的程序。算法的步伐是稳定的匹配,因为没有任何不相配的人更喜欢与目前的伙伴相配对(尽管他们有表示的偏好)。Roth [1984年] 提供了证据,只有稳定的匹配才可能持续到时间。此外,匹配的匹配是学生-多数的排序方案。此外,我们根据目前的排序和最后的排序方案,我们将进行。