Detecting hidden confounding is crucial for reliable causal analysis from observational data, directly determining which downstream causal inference method to be deployed. Inspired by the theory of higher-order regression, recent sample-efficient hypothesis testing strategies overcome the restrictive requirement of mul...
Yi-Kai Chen, Hao-Tian Wang, Yunxin Mao et al.· Proceedings of the Thirty-Fi...· 0 citations
Deep graph clustering (DGC) aims to partition graph nodes into distinct clusters in an unsupervised manner. Despite rapid advancements in this field, DGC remains inherently challenging due to the absence of ground-truth, which complicates the design of effective algorithms and impedes the establishment of standardized...
Ben-Yu Wu, Yue Liu, Qiaoyu Tan et al.· Neural Information Processin...· 4 citations
Multi-modal object re-identification (Re-ID) aims to facilitate cross-camera object retrieval in complex environments by leveraging complementary information from visual (e.g., RGB, NIR, TIR) and textual modalities. However, existing approaches often lack principled feature disentanglement and coherent multi-modal inte...
Cheng Huang, Jun-Jie Huang, Long Lan et al.· 0 citations
Multi-view clustering (MVC) relies on consistency learning to align and fuse multi-view information for building clustering decision boundaries. However, mainstream methods adopt sample-to-sample/distribution/structure similarity smoothing for consistency alignment, which builds upon continuous cluster manifolds with s...
Yuzhuo Dai, Siwei Wang, Zhibin Dong et al.· IEEE Transactions on Pattern...· 0 citations
Ontology-based Knowledge Graphs (KGs) augment entity representation through additional semantic information, facilitating link prediction for unseen entities through predefined ontology libraries. While most existing knowledge graph representation learning methods predominantly focus on co-optimizing both entities and...
Hao Li, K. Liang, Lingyuan Meng et al.· IEEE Transactions on Pattern...· 0 citations
Heterogeneous information networks (HINs) play an indispensable role in a wide range of domain-specific applications, from recommender systems to conversational platforms. Textual heterogeneous information networks (HINs) are graphs with abundant textual information. Currently, most advanced approaches to mine textual...
Yang Fang, Xiang Zhao, Daojian Zeng et al.· ACM Transactions on Informat...· 0 citations
Anchor-based methods have demonstrated significant success in multi-view clustering, particularly in handling large-scale datasets. However, existing approaches suffer from two critical limitations: (1) clustering performance is highly sensitive to the quality of initial anchors, and (2) multi-view interactions are oft...
Suyuan Liu, Siwei Wang, Ke Liang et al.· IEEE Transactions on Pattern...· 0 citations
This work proposes SpaCellAgent, an autonomous large language model (LLM) multi-agent framework that automates end-to-end spatiotemporal analysis and narrative generation and establishes a scalable, agent-driven paradigm for computational biology.
Songhan Wang, Haoang Chi, He Li et al.· Proceedings of the 32nd ACM...· 1 citation
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