19 citations · 26 across the 7 of their papers we have counts for
7 papers
Multi-factor Sequential Re-ranking with Perception-Aware Diversification
Yue Xu, Hao Chen, Zefan Wang +8
Feed recommendation systems, which recommend a sequence of items for users to browse and interact with, have gained significant popularity in practical applications. In feed produc…
Flattened Graph Convolutional Networks For Recommendation
Yue Xu, Hao Chen, Zengde Deng +2
Graph Convolutional Networks (GCNs) and their variants have achieved significant performances on various recommendation tasks. However, many existing GCN models tend to perform rec…
GPatch: Patching Graph Neural Networks for Cold-Start Recommendations
Hao Chen, Zefan Wang, Yue Xu +2
Cold start is an essential and persistent problem in recommender systems. State-of-the-art solutions rely on training hybrid models for both cold-start and existing users/items, ba…
EViT: Privacy-Preserving Image Retrieval via Encrypted Vision Transformer in Cloud Computing
Qihua Feng, Peiya Li, Zhixun Lu +5
Image retrieval systems help users to browse and search among extensive images in real-time. With the rise of cloud computing, retrieval tasks are usually outsourced to cloud serve…
Neighbor Enhanced Graph Convolutional Networks for Node Classification and Recommendation
Hao Chen, Zhong Huang, Yue Xu +4
The recently proposed Graph Convolutional Networks (GCNs) have achieved significantly superior performance on various graph-related tasks, such as node classification and recommend…
Hierarchical Cross-Modality Semantic Correlation Learning Model for Multimodal Summarization
Litian Zhang, Xiaoming Zhang, Junshu Pan +1
Multimodal summarization with multimodal output (MSMO) generates a summary with both textual and visual content. Multimodal news report contains heterogeneous contents, which makes…
Learning Social Image Embedding with Deep Multimodal Attention Networks
Feiran Huang, Xiaoming Zhang, Zhoujun Li +3
Learning social media data embedding by deep models has attracted extensive research interest as well as boomed a lot of applications, such as link prediction, classification, and…