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Kaize Ding
Kaize Ding
Assistant Professor of Stats & Data Science, Northwestern University
Verified email at northwestern.edu - Homepage
Title
Cited by
Cited by
Year
Deep anomaly detection on attributed networks
K Ding, J Li, R Bhanushali, H Liu
Proceedings of the 2019 SIAM International Conference on Data Mining, 594-602, 2019
3722019
Next-item recommendation with sequential hypergraphs
J Wang, K Ding, L Hong, H Liu, J Caverlee
Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020
2222020
Be more with less: Hypergraph attention networks for inductive text classification
K Ding, J Wang, J Li, D Li, H Liu
EMNLP 2020, 2020
1822020
Data augmentation for deep graph learning: A survey
K Ding, Z Xu, H Tong, H Liu
ACM SIGKDD Explorations Newsletter 24 (2), 61-77, 2022
1692022
Combating disinformation in a social media age
K Shu, A Bhattacharjee, F Alatawi, TH Nazer, K Ding, M Karami, H Liu
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (6 …, 2020
1552020
Interactive anomaly detection on attributed networks
K Ding, J Li, H Liu
Proceedings of the twelfth ACM international conference on web search and …, 2019
1442019
Graph prototypical networks for few-shot learning on attributed networks
K Ding, J Wang, J Li, K Shu, C Liu, H Liu
Proceedings of the 29th ACM International Conference on Information …, 2020
1242020
Few-shot network anomaly detection via cross-network meta-learning
K Ding, Q Zhou, H Tong, H Liu
Proceedings of the Web Conference 2021, 2448-2456, 2021
982021
Session-based recommendation with hypergraph attention networks
J Wang, K Ding, Z Zhu, J Caverlee
Proceedings of the 2021 SIAM international conference on data mining (SDM …, 2021
762021
Inductive anomaly detection on attributed networks
K Ding, J Li, N Agarwal, H Liu
Proceedings of the Twenty-Ninth International Conference on International …, 2020
692020
Graph few-shot learning with attribute matching
N Wang, M Luo, K Ding, L Zhang, J Li, Q Zheng
Proceedings of the 29th ACM International Conference on Information …, 2020
672020
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs
K Liu, Y Dou, Y Zhao, X Ding, X Hu, R Zhang, K Ding, C Chen, H Peng, ...
arXiv preprint arXiv:2206.10071, 2022
65*2022
Adagnn: Graph neural networks with adaptive frequency response filter
Y Dong, K Ding, B Jalaian, S Ji, J Li
Proceedings of the 30th ACM international conference on information …, 2021
502021
Graph few-shot class-incremental learning
Z Tan, K Ding, R Guo, H Liu
Proceedings of the fifteenth ACM international conference on web search and …, 2022
472022
Sequential recommendation for cold-start users with meta transitional learning
J Wang, K Ding, J Caverlee
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
462021
Few-shot learning on graphs
C Zhang, K Ding, J Li, X Zhang, Y Ye, NV Chawla, H Liu
arXiv preprint arXiv:2203.09308, 2022
362022
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
Y Liu, K Ding, H Liu, S Pan
WSDM 2023, 2022
322022
Pygod: A python library for graph outlier detection
K Liu, Y Dou, Y Zhao, X Ding, X Hu, R Zhang, K Ding, C Chen, H Peng, ...
arXiv preprint arXiv:2204.12095, 2022
322022
Fact-enhanced synthetic news generation
K Shu, Y Li, K Ding, H Liu
Proceedings of the AAAI Conference on Artificial Intelligence 35 (15), 13825 …, 2021
312021
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning
K Ding, J Wang, J Caverlee, H Liu
AAAI 2022, 2022
302022
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