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Machine Learning Model for Sparse PCM Completion

arXiv 2601.04366 ↗First posted 7 Jan 2026cs.LG math.OCcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 3 of its 13 references that are in the map. First posted on arXiv 7 Jan 2026.

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References · 3

  1. 2017Inductive Representation Learning on Large Graphscited by 6,303
  2. 2014Spectral Ranking using Seriationcited by 9
  3. 2021Inconsistency thresholds for incomplete pairwise comparison matricescited by 5

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