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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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06/14/2023
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy
Graph Neural Networks (GNNs) have achieved great success in modeling gra...
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02/19/2023
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers
Knowledge distillation has been shown to be a powerful model compression...
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10/08/2022
Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding
E-commerce query understanding is the process of inferring the shopping ...
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09/15/2022
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks
Graph neural network (GNN) pre-training methods have been proposed to en...
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06/15/2022
Condensing Graphs via One-Step Gradient Matching
As training deep learning models on large dataset takes a lot of time an...
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05/25/2022
MUG: Multi-human Graph Network for 3D Mesh Reconstruction from 2D Pose
Reconstructing multi-human body mesh from a single monocular image is an...
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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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08/07/2021
Jointly Attacking Graph Neural Network and its Explanations
Graph Neural Networks (GNNs) have boosted the performance for many graph...
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03/16/2021
Semi-Supervised Graph-to-Graph Translation
Graph translation is very promising research direction and has a wide ra...
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06/28/2020
Graph Convolutional Networks against Degree-Related Biases
In recent years, Graph Convolutional Networks (GCNs) show competitive pe...
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06/10/2020
Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
With the rapid growth and prevalence of social network applications (App...
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05/20/2020
Graph Structure Learning for Robust Graph Neural Networks
Graph Neural Networks (GNNs) are powerful tools in representation learni...
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11/22/2019
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values
Multivariate time series (MTS) forecasting is widely used in various dom...
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09/14/2019
Node Injection Attacks on Graphs via Reinforcement Learning
Real-world graph applications, such as advertisements and product recomm...
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08/20/2019
Robust Graph Neural Network Against Poisoning Attacks via Transfer Learning
Graph neural networks (GNNs) are widely used in many applications. Howev...
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02/25/2019
Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference
Real-time traffic volume inference is key to an intelligent city. It is ...
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01/24/2019
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction
Spatial-temporal prediction is a fundamental problem for constructing sm...
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03/03/2018
Modeling Spatial-Temporal Dynamics for Traffic Prediction
Spatial-temporal prediction has many applications such as climate foreca...
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02/23/2018