April 2, 2024, 7:44 p.m. | Shu Wu, Zekun Li, Yunyue Su, Zeyu Cui, Xiaoyu Zhang, Liang Wang

cs.LG updates on arXiv.org arxiv.org

arXiv:2105.11866v4 Announce Type: replace
Abstract: Factorization machine (FM) is a prevalent approach to modeling pairwise (second-order) feature interactions when dealing with high-dimensional sparse data. However, on the one hand, FM fails to capture higher-order feature interactions suffering from combinatorial expansion. On the other hand, taking into account interactions between every pair of features may introduce noise and degrade prediction accuracy. To solve the problems, we propose a novel approach, Graph Factorization Machine (GraphFM), by naturally representing features in the graph …

arxiv cs.ai cs.ir cs.lg factorization feature graph machines modeling type

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