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ORCIDHanghang Tong
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- affiliation: Arizona State University
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2020 – today
- 2024
[j89]Michael C. Loui, Nigel Bosch, Anita Say Chan, Jenny L. Davis
, Rochelle Gutiérrez, Jingrui He, Karrie Karahalios, Sanmi Koyejo, Ruby Mendenhall, Madelyn Rose Sanfilippo, Hanghang Tong, Lav R. Varshney, Yang Wang:
Artificial Intelligence, Social Responsibility, and the Roles of the University. Commun. ACM 67(8): 22-25 (2024)- [j88]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): 1205-1229 (2024) - [j87]He Zhang, Bang Wu, Xingliang Yuan, Shirui Pan, Hanghang Tong, Jian Pei:
Trustworthy Graph Neural Networks: Aspects, Methods, and Trends. Proc. IEEE 112(2): 97-139 (2024) - [j86]Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong:
ArieL: Adversarial Graph Contrastive Learning. ACM Trans. Knowl. Discov. Data 18(4): 82:1-82:22 (2024) - [j85]Feng Xia, Renaud Lambiotte, Neil Shah, Hanghang Tong, Irwin King:
Guest Editorial: Special Issue on Graph Learning. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11630-11633 (2024) - [j84]Qing Chen, Nan Chen, Wei Shuai, Guande Wu, Zhe Xu, Hanghang Tong, Nan Cao:
Calliope-Net: Automatic Generation of Graph Data Facts via Annotated Node-Link Diagrams. IEEE Trans. Vis. Comput. Graph. 30(1): 562-572 (2024) - [c272]Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong:
Sterling: Synergistic Representation Learning on Bipartite Graphs. AAAI 2024: 12976-12984 - [c271]Zhichen Zeng, Boxin Du, Si Zhang, Yinglong Xia, Zhining Liu, Hanghang Tong:
Hierarchical Multi-Marginal Optimal Transport for Network Alignment. AAAI 2024: 16660-16668 - [c270]Lihui Liu, Blaine Hill, Boxin Du, Fei Wang, Hanghang Tong:
Conversational Question Answering with Language Models Generated Reformulations over Knowledge Graph. ACL (Findings) 2024: 839-850 - [c269]Qineng Wang, Zihao Wang, Ying Su, Hanghang Tong, Yangqiu Song:
Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key? ACL (1) 2024: 6106-6131 - [c268]Xinyu He, Jian Kang, Ruizhong Qiu, Fei Wang, Jose Sepulveda, Hanghang Tong:
On the Sensitivity of Individual Fairness: Measures and Robust Algorithms. CIKM 2024: 829-838 - [c267]Yuchen Yan, Yongyi Hu, Qinghai Zhou, Shurang Wu, Dingsu Wang, Hanghang Tong:
Topological Anonymous Walk Embedding: A New Structural Node Embedding Approach. CIKM 2024: 2796-2806 - [c266]Qinghai Zhou, Yuzhong Chen, Zhe Xu, Yuhang Wu, Menghai Pan, Mahashweta Das, Hao Yang, Hanghang Tong:
Graph Anomaly Detection with Adaptive Node Mixup. CIKM 2024: 3494-3504 - [c265]Jiejun Xu, Hanghang Tong, Andrea L. Bertozzi:
The 8th Workshop on Graph Techniques for Adversarial Activity Analytics (GTA3 2024). CIKM 2024: 5603-5604 - [c264]Yao Xu, Shizhu He, Jiabei Chen, Zihao Wang, Yangqiu Song, Hanghang Tong, Guang Liu, Jun Zhao, Kang Liu:
Generate-on-Graph: Treat LLM as both Agent and KG for Incomplete Knowledge Graph Question Answering. EMNLP 2024: 18410-18430 - [c263]Eunice Chan, Zhining Liu, Ruizhong Qiu, Yuheng Zhang, Ross Maciejewski, Hanghang Tong:
Group Fairness via Group Consensus. FAccT 2024: 1788-1808 - [c262]Jinning Li, Ruipeng Han, Chenkai Sun, Dachun Sun, Ruijie Wang, Jingying Zeng, Yuchen Yan, Hanghang Tong, Tarek F. Abdelzaher:
Large Language Model-Guided Disentangled Belief Representation Learning on Polarized Social Graphs. ICCCN 2024: 1-9 - [c261]Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He:
Fairgen: Towards Fair Graph Generation. ICDE 2024: 2285-2297 - [c260]Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He:
Neural Active Learning Beyond Bandits. ICLR 2024 - [c259]Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong:
Deceptive Fairness Attacks on Graphs via Meta Learning. ICLR 2024 - [c258]Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong:
Class-Imbalanced Graph Learning without Class Rebalancing. ICML 2024 - [c257]Ruizhong Qiu, Hanghang Tong:
Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization. ICML 2024 - [c256]Haobo Xu, Yuchen Yan, Dingsu Wang, Zhe Xu, Zhichen Zeng, Tarek F. Abdelzaher, Jiawei Han, Hanghang Tong:
SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter. ICML 2024 - [c255]Zhichen Zeng, Ruizhong Qiu, Zhe Xu, Zhining Liu, Yuchen Yan, Tianxin Wei, Lei Ying, Jingrui He, Hanghang Tong:
Graph Mixup on Approximate Gromov-Wasserstein Geodesics. ICML 2024 - [c254]Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik F. Hamann, Hanghang Tong:
AIM: Attributing, Interpreting, Mitigating Data Unfairness. KDD 2024: 2014-2025 - [c253]Jun Wu, Jingrui He, Hanghang Tong:
Distributional Network of Networks for Modeling Data Heterogeneity. KDD 2024: 3379-3390 - [c252]Lecheng Zheng, Baoyu Jing, Zihao Li, Hanghang Tong, Jingrui He:
Heterogeneous Contrastive Learning for Foundation Models and Beyond. KDD 2024: 6666-6676 - [c251]Chuxuan Hu, Qinghai Zhou, Hanghang Tong:
Genius: Subteam Replacement with Clustering-based Graph Neural Networks. SDM 2024: 10-18 - [c250]Huiyuan Chen, Zhe Xu, Chin-Chia Michael Yeh, Vivian Lai, Yan Zheng, Minghua Xu, Hanghang Tong:
Masked Graph Transformer for Large-Scale Recommendation. SIGIR 2024: 2502-2506 - [c249]Blaine Hill, Lihui Liu, Hanghang Tong:
Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform. WSDM 2024: 1066-1069 - [c248]Lihui Liu, Zihao Wang, Jiaxin Bai, Yangqiu Song, Hanghang Tong:
New Frontiers of Knowledge Graph Reasoning: Recent Advances and Future Trends. WWW (Companion Volume) 2024: 1294-1297 - [c247]Yuchen Yan, Yongyi Hu, Qinghai Zhou, Lihui Liu, Zhichen Zeng, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hanghang Tong:
PaCEr: Network Embedding From Positional to Structural. WWW 2024: 2485-2496 - [c246]Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong:
Ensuring User-side Fairness in Dynamic Recommender Systems. WWW 2024: 3667-3678 - [i107]Weilin Cong, Jian Kang, Hanghang Tong, Mehrdad Mahdavi:
On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method. CoRR abs/2402.16387 (2024) - [i106]Qineng Wang, Zihao Wang, Ying Su, Hanghang Tong, Yangqiu Song:
Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key? CoRR abs/2402.18272 (2024) - [i105]Weizhi Fei, Zihao Wang, Hang Yin, Yang Duan, Hanghang Tong, Yangqiu Song:
Soft Reasoning on Uncertain Knowledge Graphs. CoRR abs/2403.01508 (2024) - [i104]Lecheng Zheng, Baoyu Jing, Zihao Li, Hanghang Tong, Jingrui He:
Heterogeneous Contrastive Learning for Foundation Models and Beyond. CoRR abs/2404.00225 (2024) - [i103]Lihui Liu, Zihao Wang, Ruizhong Qiu, Yikun Ban, Eunice Chan, Yangqiu Song, Jingrui He, Hanghang Tong:
Logic Query of Thoughts: Guiding Large Language Models to Answer Complex Logic Queries with Knowledge Graphs. CoRR abs/2404.04264 (2024) - [i102]Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He:
Neural Active Learning Beyond Bandits. CoRR abs/2404.12522 (2024) - [i101]Yao Xu, Shizhu He, Jiabei Chen, Zihao Wang, Yangqiu Song, Hanghang Tong, Kang Liu, Jun Zhao:
Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question Answering. CoRR abs/2404.14741 (2024) - [i100]Huiyuan Chen, Zhe Xu, Chin-Chia Michael Yeh, Vivian Lai, Yan Zheng, Minghua Xu, Hanghang Tong:
Masked Graph Transformer for Large-Scale Recommendation. CoRR abs/2405.04028 (2024) - [i99]Zhe Xu, Ruizhong Qiu, Yuzhong Chen, Huiyuan Chen, Xiran Fan, Menghai Pan, Zhichen Zeng, Mahashweta Das, Hanghang Tong:
Discrete-state Continuous-time Diffusion for Graph Generation. CoRR abs/2405.11416 (2024) - [i98]Ruizhong Qiu, Hanghang Tong:
Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization. CoRR abs/2405.16805 (2024) - [i97]Ruizhong Qiu, Weiliang Will Zeng, Hanghang Tong, James Ezick, Christopher Lott:
How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark. CoRR abs/2406.06647 (2024) - [i96]Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik F. Hamann, Hanghang Tong:
AIM: Attributing, Interpreting, Mitigating Data Unfairness. CoRR abs/2406.08819 (2024) - [i95]Xiaodong Yang, Huiyuan Chen, Yuchen Yan, Yuxin Tang, Yuying Zhao, Eric Xu, Yiwei Cai, Hanghang Tong:
SimCE: Simplifying Cross-Entropy Loss for Collaborative Filtering. CoRR abs/2406.16170 (2024) - [i94]Zexing Xu, Linjun Zhang, Sitan Yang, S. Rasoul Etesami, Hanghang Tong, Huan Zhang, Jiawei Han:
F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data. CoRR abs/2406.16221 (2024) - [i93]Dongqi Fu, Yada Zhu, Hanghang Tong, Kommy Weldemariam, Onkar Bhardwaj, Jingrui He:
Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection. CoRR abs/2408.04254 (2024) - [i92]Hezhe Qiao, Hanghang Tong, Bo An, Irwin King, Charu C. Aggarwal, Guansong Pang:
Deep Graph Anomaly Detection: A Survey and New Perspectives. CoRR abs/2409.09957 (2024) - [i91]Xiao Lin, Zhining Liu, Dongqi Fu, Ruizhong Qiu, Hanghang Tong:
BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting. CoRR abs/2410.02195 (2024) - [i90]Zhe Xu, Kaveh Hassani, Si Zhang, Hanqing Zeng, Michihiro Yasunaga, Limei Wang, Dongqi Fu, Ning Yao, Bo Long, Hanghang Tong:
Language Models are Graph Learners. CoRR abs/2410.02296 (2024) - [i89]Lingjie Chen, Ruizhong Qiu, Siyu Yuan, Zhining Liu, Tianxin Wei, Hyunsik Yoo, Zhichen Zeng, Deqing Yang, Hanghang Tong:
WAPITI: A Watermark for Finetuned Open-Source LLMs. CoRR abs/2410.06467 (2024) - [i88]Wenxuan Bao, Zhichen Zeng, Zhining Liu, Hanghang Tong, Jingrui He:
AdaRC: Mitigating Graph Structure Shifts during Test-Time. CoRR abs/2410.06976 (2024) - [i87]Dongqi Fu, Liri Fang, Zihao Li, Hanghang Tong, Vetle I. Torvik, Jingrui He:
Parametric Graph Representations in the Era of Foundation Models: A Survey and Position. CoRR abs/2410.12126 (2024) - [i86]Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He:
PageRank Bandits for Link Prediction. CoRR abs/2411.01410 (2024) - [i85]Ruizhong Qiu, Zhe Xu, Wenxuan Bao, Hanghang Tong:
Ask, and it shall be given: Turing completeness of prompting. CoRR abs/2411.01992 (2024) - 2023
- [j83]Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang, Hanghang Tong, Jiawei Han:
Embedding text-rich graph neural networks with sequence and topical semantic structures. Knowl. Inf. Syst. 65(2): 613-640 (2023) - [j82]Dongqi Fu, Wenxuan Bao, Ross Maciejewski, Hanghang Tong, Jingrui He:
Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey. SIGKDD Explor. 25(1): 54-72 (2023) - [j81]Lei Shi, Yuankai Luo, Shuai Ma, Hanghang Tong, Zhetao Li, Xiatian Zhang, Zhiguang Shan:
Mobility Inference on Long-Tailed Sparse Trajectory. ACM Trans. Intell. Syst. Technol. 14(1): 18:1-18:26 (2023) - [j80]Qinghai Zhou, Liangyue Li, Nan Cao, Lei Ying, Hanghang Tong:
Adversarial Attacks on Multi-Network Mining: Problem Definition and Fast Solutions. IEEE Trans. Knowl. Data Eng. 35(1): 96-107 (2023) - [j79]Hao Wang, Defu Lian, Hanghang Tong, Qi Liu, Zhenya Huang, Enhong Chen:
Decoupled Representation Learning for Attributed Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2430-2444 (2023) - [j78]Scott Freitas, Diyi Yang, Srijan Kumar, Hanghang Tong, Duen Horng Chau:
Graph Vulnerability and Robustness: A Survey. IEEE Trans. Knowl. Data Eng. 35(6): 5915-5934 (2023) - [j77]Ziye Zhu, Hanghang Tong, Yu Wang, Yun Li:
BL-GAN: Semi-Supervised Bug Localization via Generative Adversarial Network. IEEE Trans. Knowl. Data Eng. 35(11): 11112-11125 (2023) - [j76]Haibo Ye, Xinjie Li, Yuan Yao, Hanghang Tong:
Towards Robust Neural Graph Collaborative Filtering via Structure Denoising and Embedding Perturbation. ACM Trans. Inf. Syst. 41(3): 59:1-59:28 (2023) - [j75]Senrong Xu, Liangyue Li, Zenan Li, Yuan Yao, Feng Xu, Zulong Chen, Quan Lu, Hanghang Tong:
On the Vulnerability of Graph Learning-based Collaborative Filtering. ACM Trans. Inf. Syst. 41(4): 87:1-87:28 (2023) - [c245]Ruijie Wang, Baoyu Li, Yichen Lu, Dachun Sun, Jinning Li, Yuchen Yan, Shengzhong Liu, Hanghang Tong, Tarek F. Abdelzaher:
Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning. ACL (Findings) 2023: 2440-2457 - [c244]Haipeng Luo, Hanghang Tong, Mengxiao Zhang, Yuheng Zhang:
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs. ALT 2023: 1074-1100 - [c243]Qinghai Zhou, Kaize Ding, Huan Liu, Hanghang Tong:
Learning Node Abnormality with Weak Supervision. CIKM 2023: 3584-3594 - [c242]Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong:
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network. CIKM 2023: 3860-3864 - [c241]Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi:
Do We Really Need Complicated Model Architectures For Temporal Networks? ICLR 2023 - [c240]Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong, Heng Ji:
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning. ICLR 2023 - [c239]Zhichen Zeng, Ruike Zhu, Yinglong Xia, Hanqing Zeng, Hanghang Tong:
Generative Graph Dictionary Learning. ICML 2023: 40749-40769 - [c238]Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong:
Reconstructing Graph Diffusion History from a Single Snapshot. KDD 2023: 1978-1988 - [c237]Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong:
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders. KDD 2023: 2256-2268 - [c236]Zhe Xu, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hao Yang, Hanghang Tong:
Kernel Ridge Regression-Based Graph Dataset Distillation. KDD 2023: 2850-2861 - [c235]Zhe Xu, Yuzhong Chen, Qinghai Zhou, Yuhang Wu, Menghai Pan, Hao Yang, Hanghang Tong:
Node Classification Beyond Homophily: Towards a General Solution. KDD 2023: 2862-2873 - [c234]Lihui Liu, Hanghang Tong:
Knowledge Graph Reasoning and Its Applications. KDD 2023: 5813-5814 - [c233]Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong:
BeMap: Balanced Message Passing for Fair Graph Neural Network. LoG 2023: 37 - [c232]Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong:
From Trainable Negative Depth to Edge Heterophily in Graphs. NeurIPS 2023 - [c231]Yuchen Yan, Baoyu Jing, Lihui Liu, Ruijie Wang, Jinning Li, Tarek F. Abdelzaher, Hanghang Tong:
Reconciling Competing Sampling Strategies of Network Embedding. NeurIPS 2023 - [c230]Si Zhang, Yinglong Xia, Yan Zhu, Hanghang Tong:
Representation Learning on Dynamic Network of Networks. SDM 2023: 298-306 - [c229]Shengyu Feng, Hanghang Tong:
Concept Discovery for Fast Adaptation. SDM 2023: 577-585 - [c228]Senrong Xu, Liangyue Li, Yuan Yao, Zulong Chen, Han Wu, Quan Lu, Hanghang Tong:
MUSENET: Multi-Scenario Learning for Repeat-Aware Personalized Recommendation. WSDM 2023: 517-525 - [c227]Dongqi Fu, Zhe Xu, Hanghang Tong, Jingrui He:
Natural and Artificial Dynamics in GNNs: A Tutorial. WSDM 2023: 1252-1255 - [c226]Zhichen Zeng, Si Zhang, Yinglong Xia, Hanghang Tong:
PARROT: Position-Aware Regularized Optimal Transport for Network Alignment. WWW 2023: 372-382 - [c225]Yun-Yong Ko, Seongeun Ryu, Soeun Han, Youngseung Jeon, Jaehoon Kim, Sohyun Park, Kyungsik Han, Hanghang Tong, Sang-Wook Kim:
KHAN: Knowledge-Aware Hierarchical Attention Networks for Accurate Political Stance Prediction. WWW 2023: 1572-1583 - [c224]Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong:
Knowledge Graph Question Answering with Ambiguous Query. WWW 2023: 2477-2486 - [i84]Shengyu Feng, Hanghang Tong:
Concept Discovery for Fast Adapatation. CoRR abs/2301.07850 (2023) - [i83]Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong:
STERLING: Synergistic Representation Learning on Bipartite Graphs. CoRR abs/2302.05428 (2023) - [i82]Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi:
Do We Really Need Complicated Model Architectures For Temporal Networks? CoRR abs/2302.11636 (2023) - [i81]Yun-Yong Ko, Seongeun Ryu, Soeun Han, Yeongseung Jeon, Jaehoon Kim, Sohyun Park, Kyungsik Han, Hanghang Tong, Sang-Wook Kim:
KHAN: Knowledge-Aware Hierarchical Attention Networks for Political Stance Prediction. CoRR abs/2302.12126 (2023) - [i80]Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He:
FairGen: Towards Fair Graph Generation. CoRR abs/2303.17743 (2023) - [i79]Boxin Du, Lihui Liu, Jiejun Xu, Fei Wang, Hanghang Tong:
Neural Multi-network Diffusion towards Social Recommendation. CoRR abs/2304.04994 (2023) - [i78]Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong, Heng Ji:
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning. CoRR abs/2305.12738 (2023) - [i77]Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew J. Margenot, Hanghang Tong:
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders. CoRR abs/2305.18612 (2023) - [i76]Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong:
Reconstructing Graph Diffusion History from a Single Snapshot. CoRR abs/2306.00488 (2023) - [i75]Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong:
BeMap: Balanced Message Passing for Fair Graph Neural Network. CoRR abs/2306.04107 (2023) - [i74]Ruijie Wang, Baoyu Li, Yichen Lu, Dachun Sun, Jinning Li, Yuchen Yan, Shengzhong Liu, Hanghang Tong, Tarek F. Abdelzaher:
Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning. CoRR abs/2306.07512 (2023) - [i73]Dongqi Fu, Wenxuan Bao, Ross Maciejewski, Hanghang Tong, Jingrui He:
Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey. CoRR abs/2307.04338 (2023) - [i72]Qing Chen, Nan Chen, Wei Shuai, Guande Wu, Zhe Xu, Hanghang Tong, Nan Cao:
Calliope-Net: Automatic Generation of Graph Data Facts via Annotated Node-link Diagrams. CoRR abs/2308.06441 (2023) - [i71]Zhining Liu, Zhichen Zeng, Ruizhong Qiu, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong:
Topological Augmentation for Class-Imbalanced Node Classification. CoRR abs/2308.14181 (2023) - [i70]Hyunsik Yoo, Zhichen Zeng, Jian Kang, Zhining Liu, David Zhou, Fei Wang, Eunice Chan, Hanghang Tong:
Ensuring User-side Fairness in Dynamic Recommender Systems. CoRR abs/2308.15651 (2023) - [i69]Yun-Yong Ko, Hanghang Tong, Sang-Wook Kim:
Enhancing Hyperedge Prediction with Context-Aware Self-Supervised Learning. CoRR abs/2309.05798 (2023) - [i68]Haibo Ye, Xinjie Li, Yuan Yao, Hanghang Tong:
On the Sweet Spot of Contrastive Views for Knowledge-enhanced Recommendation. CoRR abs/2309.13384 (2023) - [i67]Zihao Wang, Yongqiang Chen, Yang Duan, Weijiang Li, Bo Han, James Cheng, Hanghang Tong:
Towards out-of-distribution generalizable predictions of chemical kinetics properties. CoRR abs/2310.03152 (2023) - [i66]Zhichen Zeng, Boxin Du, Si Zhang, Yinglong Xia, Zhining Liu, Hanghang Tong:
Hierarchical Multi-Marginal Optimal Transport for Network Alignment. CoRR abs/2310.04470 (2023) - [i65]Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong:
Deceptive Fairness Attacks on Graphs via Meta Learning. CoRR abs/2310.15653 (2023) - [i64]Yushun Dong, Binchi Zhang, Hanghang Tong, Jundong Li:
ELEGANT: Certified Defense on the Fairness of Graph Neural Networks. CoRR abs/2311.02757 (2023) - [i63]Zhe Xu, Menghai Pan, Yuzhong Chen, Huiyuan Chen, Yuchen Yan, Mahashweta Das, Hanghang Tong:
Invariant Graph Transformer. CoRR abs/2312.07859 (2023) - [i62]