All Stories

  1. Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
  2. Covering a Graph with Dense Subgraph Families, via Triangle-Rich Sets
  3. Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training
  4. An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce
  5. ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding
  6. Search Behavior Prediction: A Hypergraph Perspective
  7. Hyperbolic Neural Networks: Theory, Architectures and Applications
  8. Graph-based Multilingual Language Model
  9. Learning Backward Compatible Embeddings
  10. ALLIE: Active Learning on Large-scale Imbalanced Graphs
  11. Accepted Tutorials at The Web Conference 2022
  12. ANTHEM
  13. Bipartite Dynamic Representations for Abuse Detection
  14. Using hyperboloids to embed and query knowledge graphs
  15. Identifying Facet Mismatches In Search Via Micrographs