39 citations · 48 across the 5 of their papers we have counts for
5 papers
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks
Kaixiong Zhou, Xiao Huang, Daochen Zha +4
Graph neural networks (GNNs) integrate deep architectures and topological structure modeling in an effective way. However, the performance of existing GNNs would decrease significa…
HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters
Gabriel Appleby, Mateus Espadoto, Rui Chen +4
Projection algorithms such as t-SNE or UMAP are useful for the visualization of high dimensional data, but depend on hyperparameters which must be tuned carefully. Unfortunately, i…
Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation
Yanan Wang, Yong Ge, Li Li +2
Reinforcement learning (RL) has shown great promise in optimizing long-term user interest in recommender systems. However, existing RL-based recommendation methods need a large num…
Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning
Xi Liu, Li Li, Ping-Chun Hsieh +3
With the explosive growth of online products and content, recommendation techniques have been considered as an effective tool to overcome information overload, improve user experie…
Streaming Network Embedding through Local Actions
Xi Liu, Ping-Chun Hsieh, Nick Duffield +3
Recently, considerable research attention has been paid to network embedding, a popular approach to construct feature vectors of vertices. Due to the curse of dimensionality and sp…