  This paper presents a natural extension of stagewise ranking to the the case
of infinitely many items. We introduce the infinite generalized Mallows model
(IGM), describe its properties and give procedures to estimate it from data.
For estimation of multimodal distributions we introduce the
Exponential-Blurring-Mean-Shift nonparametric clustering algorithm. The
experiments highlight the properties of the new model and demonstrate that
infinite models can be simple, elegant and practical.
