6 papers
Maximal Biclique Enumeration with Improved Worst-Case Time Complexity Guarantee: A Partition-Oriented Strategy
Kaixin Wang, Kaiqiang Yu, Cheng Long
The maximal biclique enumeration problem in bipartite graphs is fundamental and has numerous applications in E-commerce and transaction networks. Most existing studies adopt a bran…
Maximum Degree-Based Quasi-Clique Search via an Iterative Framework
Hongbo Xia, Kaiqiang Yu, Shengxin Liu +2
Cohesive subgraph mining is a fundamental problem in graph theory with numerous real-world applications, such as social network analysis and protein-protein interaction modeling. A…
Temporal -Core Query, Revisited
Yinyu Liu, Kaiqiang Yu, Shengxin Liu +2
Querying cohesive subgraphs in temporal graphs is essential for understanding the dynamic structure of real-world networks, such as evolving communities in social platforms, shifti…
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang, Cheng Long, Yongyi Mao
Federated learning (FL) is a widely adopted privacy-preserving distributed learning framework, yet its generalization performance remains less explored compared to centralized lear…
Fast Maximum Common Subgraph Search: A Redundancy-Reduced Backtracking Approach
Kaiqiang Yu, Kaixin Wang, Cheng Long +2
Given two input graphs, finding the largest subgraph that occurs in both, i.e., finding the maximum common subgraph, is a fundamental operator for evaluating the similarity between…
Maximal Clique Enumeration with Hybrid Branching and Early Termination
Kaixin Wang, Kaiqiang Yu, Cheng Long
Maximal clique enumeration (MCE) is crucial for tasks like community detection and biological network analysis. Existing algorithms typically adopt the branch-and-bound framework w…