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08/06/2023
Communication-Free Distributed GNN Training with Vertex Cut
Training Graph Neural Networks (GNNs) on real-world graphs consisting of...
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07/19/2023
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
Modeling customer shopping intentions is a crucial task for e-commerce, ...
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05/17/2023
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
Distributed training of GNNs enables learning on massive graphs (e.g., s...
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02/27/2023
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction
Link prediction is central to many real-world applications, but its perf...
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11/23/2022
Search Behavior Prediction: A Hypergraph Perspective
Although the bipartite shopping graphs are straightforward to model sear...
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10/26/2022
TuneUp: A Training Strategy for Improving Generalization of Graph Neural Networks
Despite many advances in Graph Neural Networks (GNNs), their training st...
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07/06/2022
Text Enriched Sparse Hyperbolic Graph Convolutional Networks
Heterogeneous networks, which connect informative nodes containing text ...
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06/14/2022
Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search
Improving the quality of search results can significantly enhance users ...
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06/07/2022
Learning Backward Compatible Embeddings
Embeddings, low-dimensional vector representation of objects, are fundam...
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03/28/2022
Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
Predicting missing facts in a knowledge graph (KG) is crucial as modern ...
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02/16/2022
Task-Agnostic Graph Explanations
Graph Neural Networks (GNNs) have emerged as powerful tools to encode gr...
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11/08/2021
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
Graph Neural Networks (GNNs) have achieved state of the art performance ...
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10/26/2021
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
Logical reasoning over Knowledge Graphs (KGs) is a fundamental technique...
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09/05/2021
Scalable Feature Selection for (Multitask) Gradient Boosted Trees
Gradient Boosted Decision Trees (GBDTs) are widely used for building ran...
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12/23/2020
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs
Knowledge Graphs (KGs) are ubiquitous structures for information storage...
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05/07/2020