4 citations · 5 across the 4 of their papers we have counts for
7 papers
Fast Generating A Large Number of Gumbel-Max Variables
Yiyan Qi, Pinghui Wang, Yuanming Zhang +3
The well-known Gumbel-Max Trick for sampling elements from a categorical distribution (or more generally a nonnegative vector) and its variants have been widely used in areas such…
MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
Nuo Xu, Pinghui Wang, Long Chen +2
Predicting interactions between structured entities lies at the core of numerous tasks such as drug regimen and new material design. In recent years, graph neural networks have bec…
Submodular Optimization Over Streams with Inhomogeneous Decays
Junzhou Zhao, Shuo Shang, Pinghui Wang +2
Cardinality constrained submodular function maximization, which aims to select a subset of size at most to maximize a monotone submodular utility function, is the key in many d…
Tracking Influential Nodes in Time-Decaying Dynamic Interaction Networks
Junzhou Zhao, Shuo Shang, Pinghui Wang +2
Identifying influential nodes that can jointly trigger the maximum influence spread in networks is a fundamental problem in many applications such as viral marketing, online advert…
Tracking Triadic Cardinality Distributions for Burst Detection in High-Speed Multigraph Streams
Junzhou Zhao, Pinghui Wang, John C. S. Lui +2
In everyday life, we often observe unusually frequent interactions among people before or during important events, e.g., people send/receive more greetings to/from their friends on…
Sampling Online Social Networks by Random Walk with Indirect Jumps
Junzhou Zhao, Pinghui Wang, John C. S. Lui +2
Random walk-based sampling methods are gaining popularity and importance in characterizing large networks. While powerful, they suffer from the slow mixing problem when the graph i…