Composite Marginal Likelihood Methods for Random Utility Models

Zhibing Zhao, Lirong Xia

Abstract: We propose a novel and flexible rank-breaking-then-composite-marginal-likelihood (RBCML) framework for learning random utility models (RUMs), which include the Plackett-Luce model. We characterize ...