Estimation and Clustering with Infinite Rankings
Abstract
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.
Cite
Text
Meila and Bao. "Estimation and Clustering with Infinite Rankings." Conference on Uncertainty in Artificial Intelligence, 2008.Markdown
[Meila and Bao. "Estimation and Clustering with Infinite Rankings." Conference on Uncertainty in Artificial Intelligence, 2008.](https://mlanthology.org/uai/2008/meila2008uai-estimation/)BibTeX
@inproceedings{meila2008uai-estimation,
title = {{Estimation and Clustering with Infinite Rankings}},
author = {Meila, Marina and Bao, Le},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2008},
pages = {393-402},
url = {https://mlanthology.org/uai/2008/meila2008uai-estimation/}
}