Lagrangian Inference for Ranking Problems
提出一种拉格朗日推断框架，用于回答物品间的排序问题（如A是否优于B、是否在前10），提供理论最优性保证，并在大规模电影排名数据上验证了方法。
Understanding ranking orders of different items is of great importance in many applications such as sports, online game, and recommendation, among many others. This paper provides a novel approach to inferring the ranking systems. In particular, the paper aims to answer questions like, is item A better than item B? Is item A among the top 10 items? Such inference problems are challenging as they involve combinatorial structures. The key technical innovation is a new Lagrangian inference framework with new bootstrap tools. Strong theoretical guarantees are provided showing the optimality of the proposed method. A novel application of inferring movies’ ranking using a large-scale data set is provided to demonstrate the applicability of the proposed method.