Kaize Ding

ORCID

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 104

Top Venues

Publications

Shuhan Liu, Kaize Ding
Beyond Generalization: A Survey of Out-Of-Distribution Adaptation on Graphs. CoRR (2024)
Guangyao Dou, Zheyuan Liu, Qing Lyu, Kaize Ding, Eric Wong
Avoiding Copyright Infringement via Machine Unlearning. CoRR (2024)
Kaize Ding, Xiaoxiao Ma, Yixin Liu, Shirui Pan
Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise. KDD (2024)
Yichuan Li, Kaize Ding, Jianling Wang, Kyumin Lee
Empowering Large Language Models for Textual Data Augmentation. ACL (Findings) (2024)
Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, Fan Yang, Mengnan Du, Yongfeng Zhang
Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers? CoRR (2024)
Zhangsihao Yang, Kaize Ding, Huan Liu, Yalin Wang
MGM-AE: Self-Supervised Learning on 3D Shape Using Mesh Graph Masked Autoencoders. WACV (2024)
Wenjing Chang, Kay Liu, Kaize Ding, Philip S. Yu, Jianjun Yu
Multitask Active Learning for Graph Anomaly Detection. CoRR (2024)
Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu
Robust Graph Meta-Learning for Weakly Supervised Few-Shot Node Classification. ACM Trans. Knowl. Discov. Data 18 (4) (2024)
Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, Hanghang Tong
Generalized few-shot node classification: toward an uncertainty-based solution. Knowl. Inf. Syst. 66 (2) (2024)
Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed
The 5th International Workshop on Machine Learning on Graphs (MLoG). WSDM (2024)
Wenjie Du, Jun Wang, Linglong Qian, Yiyuan Yang, Fanxing Liu, Zepu Wang, Zina M. Ibrahim, Haoxin Liu, Zhiyuan Zhao, Yingjie Zhou, Wenjia Wang, Kaize Ding, Yuxuan Liang, B. Aditya Prakash, Qingsong Wen
TSI-Bench: Benchmarking Time Series Imputation. CoRR (2024)
Qingcheng Zeng, Mingyu Jin, Qinkai Yu, Zhenting Wang, Wenyue Hua, Zihao Zhou, Guangyan Sun, Yanda Meng, Shiqing Ma, Qifan Wang, Felix Juefei-Xu, Kaize Ding, Fan Yang, Ruixiang Tang, Yongfeng Zhang
Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models. CoRR (2024)
Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Wei Cheng, Si Zhang, Yonghui Fan, Liqing Zhang, Dawei Zhou
Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization. KDD (2024)
Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong
Sterling: Synergistic Representation Learning on Bipartite Graphs. AAAI (2024)
Xiaoxiao Ma, Ruikun Li, Fanzhen Liu, Kaize Ding, Jian Yang, Jia Wu
Graph Anomaly Detection with Few Labels: A Data-Centric Approach. KDD (2024)
Yili Wang, Yixin Liu, Xu Shen, Chenyu Li, Kaize Ding, Rui Miao, Ying Wang, Shirui Pan, Xin Wang
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark. CoRR (2024)
Yichuan Li, Kaize Ding, Jianling Wang, Kyumin Lee
Empowering Large Language Models for Textual Data Augmentation. CoRR (2024)
Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu
RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD (2024)
Kaize Ding
Data-Efficient Graph Learning. AAAI (2024)
Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong
STERLING: Synergistic Representation Learning on Bipartite Graphs. CoRR (2023)
Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu
Virtual Node Tuning for Few-shot Node Classification. KDD (2023)
Yichuan Li, Kaize Ding, Kyumin Lee
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs. CoRR (2023)
Yichuan Li, Kaize Ding, Kyumin Lee
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs. EMNLP (Findings) (2023)
Paras Sheth, Ahmadreza Mosallanezhad, Kaize Ding, Reepal Shah, John Sabo, Huan Liu, K. Selçuk Candan
STREAMS: Towards Spatio-Temporal Causal Discovery with Reinforcement Learning for Streamflow Rate Prediction. CIKM (2023)
Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu
MetaGAD: Learning to Meta Transfer for Few-shot Graph Anomaly Detection. CoRR (2023)
Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. SIGIR (2023)
Qinghai Zhou, Kaize Ding, Huan Liu, Hanghang Tong
Learning Node Abnormality with Weak Supervision. CIKM (2023)
Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu
Virtual Node Tuning for Few-shot Node Classification. CoRR (2023)
Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan
Towards Self-Interpretable Graph-Level Anomaly Detection. NeurIPS (2023)
Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li
Federated Few-shot Learning. CoRR (2023)
Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li
Few-shot Node Classification with Extremely Weak Supervision. WSDM (2023)
Kaize Ding, Albert Jiongqian Liang, Bryan Perrozi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. CoRR (2023)
Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan
Towards Self-Interpretable Graph-Level Anomaly Detection. CoRR (2023)
Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning. AAAI (2023)
Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li
Few-shot Node Classification with Extremely Weak Supervision. CoRR (2023)
Yixin Liu, Kaize Ding, Jianling Wang, Vincent Lee, Huan Liu, Shirui Pan
Learning Strong Graph Neural Networks with Weak Information. CoRR (2023)
Zhangsihao Yang, Mengwei Ren, Kaize Ding, Guido Gerig, Yalin Wang
Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation. CoRR (2023)
Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection. WSDM (2023)
Shuyi Chen, Kaize Ding, Shixiang Zhu
Uncertainty-Aware Robust Learning on Noisy Graphs. CoRR (2023)
Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Dawei Zhou
Characterizing Long-Tail Categories on Graphs. CoRR (2023)
Zhangsihao Yang, Mengwei Ren, Kaize Ding, Guido Gerig, Yalin Wang
Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation. NeurIPS (2023)
Yixin Liu, Kaize Ding, Jianling Wang, Vincent C. S. Lee, Huan Liu, Shirui Pan
Learning Strong Graph Neural Networks with Weak Information. KDD (2023)
Suraj Jyothi Unni, Paras Sheth, Kaize Ding, Huan Liu, K. Selçuk Candan
UPREVE: An End-to-End Causal Discovery Benchmarking System. CoRR (2023)
Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li
Federated Few-shot Learning. KDD (2023)
Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. Big Data (2022)
Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li
Task-Adaptive Few-shot Node Classification. CoRR (2022)
Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li
Task-Adaptive Few-shot Node Classification. KDD (2022)
Kaize Ding, Jundong Li, Nitesh V. Chawla, Huan Liu
Graph Minimally-supervised Learning. WSDM (2022)
Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu
Structural and Semantic Contrastive Learning for Self-supervised Node Representation Learning. CoRR (2022)
Kaize Ding, Chuxu Zhang, Jie Tang, Nitesh V. Chawla, Huan Liu
Toward Graph Minimally-Supervised Learning. KDD (2022)
Kaize Ding, Zhe Xu, Hanghang Tong, Huan Liu
Data Augmentation for Deep Graph Learning: A Survey. SIGKDD Explor. 24 (2) (2022)
Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu
Few-Shot Learning on Graphs. IJCAI (2022)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
Graph Few-shot Class-incremental Learning. WSDM (2022)
Kaize Ding, Zhe Xu, Hanghang Tong, Huan Liu
Data Augmentation for Deep Graph Learning: A Survey. CoRR (2022)
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. NeurIPS (2022)
Zhen Tan, Song Wang, Kaize Ding, Jundong Li, Huan Liu
Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification. CoRR (2022)
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu
Benchmarking Node Outlier Detection on Graphs. CoRR (2022)
Zhen Tan, Song Wang, Kaize Ding, Jundong Li, Huan Liu
Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification. LoG (2022)
Ujun Jeong, Zeyad Alghamdi, Kaize Ding, Lu Cheng, Baoxin Li, Huan Liu
Classifying COVID-19 Related Meta Ads Using Discourse Representation Through a Hypergraph. SBP-BRiMS (2022)
Kaize Ding, Elnaz Nouri, Guoqing Zheng, Huan Liu, Ryen White
Learning with Few Labeled Nodes via Augmented Graph Self-Training. CoRR (2022)
Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selçuk Candan, Huan Liu
Causal Disentanglement with Network Information for Debiased Recommendations. SISAP (2022)
Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection. CoRR (2022)
Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. CoRR (2022)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
Supervised Graph Contrastive Learning for Few-Shot Node Classification. ECML/PKDD (2) (2022)
Kaize Ding, Kai Shu, Xuan Shan, Jundong Li, Huan Liu
Cross-Domain Graph Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. 33 (6) (2022)
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu
PyGOD: A Python Library for Graph Outlier Detection. CoRR (2022)
Kaize Ding, Jianling Wang, James Caverlee, Huan Liu
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. AAAI (2022)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
A Simple Yet Effective Pretraining Strategy for Graph Few-shot Learning. CoRR (2022)
Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, Hanghang Tong
Generalized Few-Shot Node Classification. ICDM (2022)
Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu
Few-Shot Learning on Graphs: A Survey. CoRR (2022)
Kaize Ding, Qinghai Zhou, Hanghang Tong, Huan Liu
Few-shot Network Anomaly Detection via Cross-network Meta-learning. WWW (2021)
Kaize Ding, Xuan Shan, Huan Liu
Towards Anomaly-resistant Graph Neural Networks via Reinforcement Learning. CIKM (2021)
Kai Shu, Yichuan Li, Kaize Ding, Huan Liu
Fact-Enhanced Synthetic News Generation. AAAI (2021)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
Graph Few-shot Class-incremental Learning. CoRR (2021)
Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li
Graph Neural Networks with Adaptive Frequency Response Filter. CoRR (2021)
Kaize Ding, Dingcheng Li, Alexander Hanbo Li, Xing Fan, Chenlei Guo, Yang Liu, Huan Liu
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation. EMNLP (1) (2021)
Kaize Ding, Qinghai Zhou, Hanghang Tong, Huan Liu
Few-shot Network Anomaly Detection via Cross-network Meta-learning. CoRR (2021)
Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu
Weakly-supervised Graph Meta-learning for Few-shot Node Classification. CoRR (2021)
Xuan Shan, Chuanjie Liu, Yiqian Xia, Qi Chen, Yusi Zhang, Kaize Ding, Yaobo Liang, Angen Luo, Yuxiang Luo
GLOW : Global Weighted Self-Attention Network for Web Search. IEEE BigData (2021)
Kaize Ding, Dingcheng Li, Alexander Hanbo Li, Xing Fan, Chenlei Guo, Yang Liu, Huan Liu
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation. CoRR (2021)
Kaize Ding, Jianling Wang, James Caverlee, Huan Liu
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. CoRR (2021)
Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee
Session-based Recommendation with Hypergraph Attention Networks. CoRR (2021)
Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li
AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter. CIKM (2021)
Ujun Jeong, Kaize Ding, Huan Liu
FBAdTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements. CoRR (2021)
Jianling Wang, Kaize Ding, James Caverlee
Sequential Recommendation for Cold-start Users with Meta Transitional Learning. SIGIR (2021)
Jianling Wang, Kaize Ding, James Caverlee
Sequential Recommendation for Cold-start Users with Meta Transitional Learning. CoRR (2021)
Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee
Session-based Recommendation with Hypergraph Attention Networks. SDM (2021)
Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, James Caverlee
Next-item Recommendation with Sequential Hypergraphs. SIGIR (2020)
Kai Shu, Amrita Bhattacharjee, Faisal Alatawi, Tahora H. Nazer, Kaize Ding, Mansooreh Karami, Huan Liu
Combating Disinformation in a Social Media Age. CoRR (2020)
Kaize Ding, Jundong Li, Nitin Agarwal, Huan Liu
Inductive Anomaly Detection on Attributed Networks. IJCAI (2020)
Ning Wang, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, Qinghua Zheng
Graph Few-shot Learning with Attribute Matching. CIKM (2020)
Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu
Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics. CoRR (2020)
Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, Huan Liu
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification. CoRR (2020)
Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu
Graph Prototypical Networks for Few-shot Learning on Attributed Networks. CoRR (2020)
Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu
Graph Prototypical Networks for Few-shot Learning on Attributed Networks. CIKM (2020)
Kai Shu, Amrita Bhattacharjee, Faisal Alatawi, Tahora H. Nazer, Kaize Ding, Mansooreh Karami, Huan Liu
Combating disinformation in a social media age. WIREs Data Mining Knowl. Discov. 10 (6) (2020)
Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, Huan Liu
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification. EMNLP (1) (2020)
Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu
Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics. CIKM (Workshops) (2020)
Kai Shu, Yichuan Li, Kaize Ding, Huan Liu
Fact-Enhanced Synthetic News Generation. CoRR (2020)
Jianling Wang, Kaize Ding, Ziwei Zhu, Yin Zhang, James Caverlee
Key Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion. WSDM (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Kaize Ding