A5062386004- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Recommender Systems and Techniques
- Multimodal Machine Learning Applications
Hong Kong University of Science and Technology
2023
University of Hong Kong
2023
University of Science and Technology Beijing
2023
Session-based recommendation (SBR) aims to predict the user's next action based on short and dynamic sessions. Recently, there has been an increasing interest in utilizing various elaborately designed graph neural networks (GNNs) capture pair-wise relationships among items, seemingly suggesting design of more complicated models is panacea for improving empirical performance. However, these achieve relatively marginal improvements with exponential growth model complexity. In this paper, we...
Many real-world graph learning tasks require handling dynamic graphs where new nodes and edges emerge. Dynamic methods commonly suffer from the catastrophic forgetting problem, knowledge learned for previous is overwritten by updates graphs. To alleviate continual are proposed. However, existing aim to learn patterns maintain old ones with same set of parameters fixed size, thus face a fundamental tradeoff between both goals. In this paper, we propose Parameter Isolation GNN (PI-GNN) on that...