142 citations · 504 across the 29 of their papers we have counts for
5 papers · 1 filter
Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning
Meng Liu, Nate Veldt, Haoyu Song +2
Hypergraph-based machine learning methods are now widely recognized as important for modeling and using higher-order and multiway relationships between data objects. Local hypergra…
F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams
Yen-Yu Chang, Pan Li, Rok Sosic +3
Edge streams are commonly used to capture interactions in dynamic networks, such as email, social, or computer networks. The problem of detecting anomalies or rare events in edge s…
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning
Pan Li, Yanbang Wang, Hongwei Wang +1
Learning representations of sets of nodes in a graph is crucial for applications ranging from node-role discovery to link prediction and molecule classification. Graph Neural Netwo…
Graph Information Bottleneck
Tailin Wu, Hongyu Ren, Pan Li +1
Representation learning of graph-structured data is challenging because both graph structure and node features carry important information. Graph Neural Networks (GNNs) provide an…
Latent Unexpected Recommendations
Pan Li, Alexander Tuzhilin
Unexpected recommender system constitutes an important tool to tackle the problem of filter bubbles and user boredom, which aims at providing unexpected and satisfying recommendati…