Shengzhong Zhang

Orcid: 0000-0003-1783-6835

According to our database1, Shengzhong Zhang authored at least 12 papers between 2019 and 2024.

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

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Robust framework to prioritize blockchain-based supply chain challenges: the fuzzy best-worst approach for multiple criteria decision-making.
Kybernetes, 2024

Your Graph Recommender is Provably a Single-view Graph Contrastive Learning.
CoRR, 2024

StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhancing Performance of Coarsened Graphs with Gradient-Matching.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Effective stabilized self-training on few-labeled graph data.
Inf. Sci., 2023

Understanding Community Bias Amplification in Graph Representation Learning.
CoRR, 2023

UNREAL: Unlabeled Nodes Retrieval and Labeling for Heavily-imbalanced Node Classification.
CoRR, 2023

Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2021
Scaling Up Graph Neural Networks Via Graph Coarsening.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020
SCE: Scalable Network Embedding from Sparsest Cut.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
A Risk-Averse Newsvendor Model Under the Framework of Uncertainty Theory.
IEEE Access, 2019


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