In this paper, we propose a machine learning model for sparse pairwise comparison matrices (PCMs), combining classical PCM approaches with graph-based learning techniques. Numerical results are provided to demonstrate the effectiveness and scalability of the proposed method.
@article{arxiv.2601.04366,
title = {Machine Learning Model for Sparse PCM Completion},
author = {Selcuk Koyuncu and Ronak Nouri and Stephen Providence},
journal= {arXiv preprint arXiv:2601.04366},
year = {2026}
}