29 results on '"Xingquan Zhu"'
Search Results
2. OpenWGL: Open-World Graph Learning.
3. Domain-Adversarial Graph Neural Networks for Text Classification.
4. Relation Structure-Aware Heterogeneous Graph Neural Network.
5. SINE: Scalable Incomplete Network Embedding.
6. Deep Structure Learning for Fraud Detection.
7. EDLT: Enabling Deep Learning for Generic Data Classification.
8. Homophily, Structure, and Content Augmented Network Representation Learning.
9. SNOC: Streaming Network Node Classification.
10. Multi-graph-view Learning for Graph Classification.
11. Document-Specific Keyphrase Extraction Using Sequential Patterns with Wildcards.
12. Transfer Learning across Networks for Collective Classification.
13. UBLF: An Upper Bound Based Approach to Discover Influential Nodes in Social Networks.
14. Multi-instance Multi-graph Dual Embedding Learning.
15. Nested Subtree Hash Kernels for Large-Scale Graph Classification over Streams.
16. Self-Taught Active Learning from Crowds.
17. How Does Research Evolve? Pattern Mining for Research Meme Cycles.
18. Enabling Fast Lazy Learning for Data Streams.
19. Classifier and Cluster Ensembles for Mining Concept Drifting Data Streams.
20. Mining Data Streams with Labeled and Unlabeled Training Examples.
21. Vague One-Class Learning for Data Streams.
22. Cleansing Noisy Data Streams.
23. Active Learning from Data Streams.
24. Lazy Bagging for Classifying Imbalanced Data.
25. Corrective Classification: Classifier Ensembling with Corrective and Diverse Base Learners.
26. Sequential Pattern Mining in Multiple Streams.
27. Cost-Guided Class Noise Handling for Effective Cost-Sensitive Learning.
28. Dynamic Classifier Selection for Effective Mining from Noisy Data Streams.
29. IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA, November 28 - Dec. 1, 2022
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