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Ding, Kaize
92  Ergebnisse:
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1

Toward Robust Graph Semi-Supervised Learning Against Extrem..:

Ding, Kaize ; Nouri, Elnaz ; Zheng, Guoqing..
IEEE Transactions on Neural Networks and Learning Systems.  , 2024
Link: https://doi.org/10.1109/..
 
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2

MGM-AE: Self-Supervised Learning on 3D Shape Using Mesh Gra..:

, In: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV),
Yang, Zhangsihao ; Ding, Kaize ; Liu, Huan. - p. 3291-3301 , 2024
Link: https://doi.org/10.1109/..
 
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3

The 5th International Workshop on Machine Learning on Graph..:

, In: Proceedings of the 17th ACM International Conference on Web Search and Data Mining,
Derr, Tyler ; Ma, Yao ; Ding, Kaize.. - p. 1210-1211 , 2024
Link: https://dl.acm.org/doi/1..
 
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4

HyperFormer: Learning Expressive Sparse Feature Representat..:

, In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval,
Ding, Kaize ; Liang, Albert Jiongqian ; Perozzi, Bryan... - p. 2062-2066 , 2023
Link: https://dl.acm.org/doi/1..
 
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5

GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection:

, In: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining,
Liu, Yixin ; Ding, Kaize ; Liu, Huan. - p. 339-347 , 2023
Link: https://dl.acm.org/doi/1..
 
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6

Federated Few-shot Learning:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Wang, Song ; Fu, Xingbo ; Ding, Kaize... - p. 2374-2385 , 2023
Link: https://dl.acm.org/doi/1..
 
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7

STREAMS: Towards Spatio-Temporal Causal Discovery with Rein..:

, In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management,
Sheth, Paras ; Mosallanezhad, Ahmadreza ; Ding, Kaize... - p. 4815-4821 , 2023
Link: https://dl.acm.org/doi/1..
 
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8

Learning Strong Graph Neural Networks with Weak Information:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Liu, Yixin ; Ding, Kaize ; Wang, Jianling... - p. 1559-1571 , 2023
Link: https://dl.acm.org/doi/1..
 
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9

Few-shot Node Classification with Extremely Weak Supervisio:

, In: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining,
Wang, Song ; Dong, Yushun ; Ding, Kaize.. - p. 276-284 , 2023
Link: https://dl.acm.org/doi/1..
 
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10

Robust Graph Meta-learning for Weakly-supervised Few-shot N..:

Ding, Kaize ; Wang, Jianling ; Li, Jundong..
ACM Transactions on Knowledge Discovery from Data.  , 2023
Link: https://doi.org/10.1145/..
 
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11

Learning Node Abnormality with Weak Supervision:

, In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management,
Zhou, Qinghai ; Ding, Kaize ; Liu, Huan. - p. 3584-3594 , 2023
Link: https://dl.acm.org/doi/1..
 
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12

Supervised Graph Contrastive Learning for Few-Shot Node Cla..:

, In: Machine Learning and Knowledge Discovery in Databases; Lecture Notes in Computer Science,
Tan, Zhen ; Ding, Kaize ; Guo, Ruocheng. - p. 394-411 , 2023
Link: https://doi.org/10.1007/..
 
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13

Virtual Node Tuning for Few-shot Node Classification:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Tan, Zhen ; Guo, Ruocheng ; Ding, Kaize. - p. 2177-2188 , 2023
Link: https://dl.acm.org/doi/1..
 
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14

Generalized few-shot node classification: toward an uncerta..:

Xu, Zhe ; Ding, Kaize ; Wang, Yu-Xiong..
Knowledge and Information Systems.  66 (2023)  2 - p. 1205-1229 , 2023
Link: https://doi.org/10.1007/..
 
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15

Graph Few-shot Class-incremental Learning:

, In: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining,
Tan, Zhen ; Ding, Kaize ; Guo, Ruocheng. - p. 987-996 , 2022
Link: https://dl.acm.org/doi/1..
 
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