Machine Learning Model for Sparse PCM Completion
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911360076480512 |
|---|---|
| author | Koyuncu, Selcuk Nouri, Ronak Providence, Stephen |
| author_facet | Koyuncu, Selcuk Nouri, Ronak Providence, Stephen |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_04366 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Machine Learning Model for Sparse PCM Completion Koyuncu, Selcuk Nouri, Ronak Providence, Stephen Machine Learning Optimization and Control 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. |
| title | Machine Learning Model for Sparse PCM Completion |
| topic | Machine Learning Optimization and Control |
| url | https://arxiv.org/abs/2601.04366 |