Sylvester Tensor Equation for Multi-Way Association
Boxin Du, Lihui Liu, Hanghang Tong
摘要
How can we identify the same or similar users from a collection of social network platforms (e.g., Facebook, Twitter, LinkedIn, etc.)? Which restaurant shall we recommend to a given user at the right time at the right location? Given a disease, which genes and drugs are most relevant? Multi-way association, which identifies strongly correlated node sets from multiple input networks, is the key to answering these questions. Despite its importance, very few multi-way association methods exist due to its high complexity. In this paper, we formulate multi-way association as a convex optimization problem, whose optimal solution can be obtained by a Sylvester tensor equation. Furthermore, we propose two fast algorithms to solve the Sylvester tensor equation, with a linear time and space complexity. We further provide theoretic analysis in terms of the sensitivity of the Sylvester tensor equation solution. Empirical evaluations demonstrate the efficacy of the proposed method.
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引用它的顶会 Paper4
- Joint Knowledge Graph Completion and Question AnsweringLihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia 等KDD 2022 · 被引用 46 次
- Hierarchical Multi-Marginal Optimal Transport for Network AlignmentZhichen Zeng, Boxin Du, Si Zhang, Yinglong Xia 等AAAI 2024 · 被引用 39 次
- Knowledge Graph Question Answering with Ambiguous QueryLihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang 等WWW 2023 · 被引用 36 次
- PURE: Positive-Unlabeled Recommendation with Generative Adversarial NetworkYao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi 等KDD 2021 · 被引用 29 次
它引用的顶会 Paper2
- Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network LearningRunzhong Wang, Junchi Yan, Xiaokang YangNeurIPS 2020 · 被引用 39 次
- PURE: Positive-Unlabeled Recommendation with Generative Adversarial NetworkYao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi 等KDD 2021 · 被引用 29 次
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