Ranking individuals by group comparisons

Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng

Abstract: This paper proposes new approaches to rank individuals from their group competition results. Many real-world problems are of this type. For example, ranking players from team games is important in some sports. We propose an exponential model to solve such problems. To estimate individual rankings through the proposed model we introduce two convex minimization formulas with easy and efficient solution procedures. Experiments on real bridge records and multi-class classification demonstrate the viability of the proposed model.