Zekun Li

Orcid: 0000-0002-1207-1901

Affiliations:
  • Institute of Information Engineering, Chinese Academy of Sciences, China


According to our database1, Zekun Li authored at least 14 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
DyGCN: Efficient Dynamic Graph Embedding With Graph Convolutional Network.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

Arbitrary-scale Super-resolution via Deep Learning: A Comprehensive Survey.
Inf. Fusion, February, 2024

SAVSR: Arbitrary-Scale Video Super-Resolution via a Learned Scale-Adaptive Network.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2021
Weakly-supervised action localization via embedding-modeling iterative optimization.
Pattern Recognit., 2021

GraphFM: Graph Factorization Machines for Feature Interaction Modeling.
CoRR, 2021

DyGCN: Dynamic Graph Embedding with Graph Convolutional Network.
CoRR, 2021

Cold-start Sequential Recommendation via Meta Learner.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Heterogeneous Graph Collaborative Filtering.
CoRR, 2020

DGTN: Dual-channel Graph Transition Network for Session-based Recommendation.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

2019
Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks.
Proceedings of the World Wide Web Conference, 2019

Semi-Supervised Compatibility Learning Across Categories for Clothing Matching.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2017
NeuroStylist: Neural Compatibility Modeling for Clothing Matching.
Proceedings of the 2017 ACM on Multimedia Conference, 2017

Clothing Matching Based on Multi-modal Data.
Proceedings of the Internet Multimedia Computing and Service, 2017


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