A Topology-aware Graph Coarsening Framework for Continual Graph Learning.
Xiaoxue Han, Zhuo Feng, Yue Ning
To appear In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS).
Vancouver, Canada. Dec. 9-15, 2024
[ Arxiv ]
Advances in Human Event Modeling: From Graph Neural Networks to Language Models.
Songgaojun Deng, Maarten de Rijke, Yue Ning
To appear In Proceedings of
the 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).
Barcelona, Spain. August 25-29, 2024
[ local copy ]
Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning.
Chang Lu, Chandan K Reddy, Ping Wang, Yue Ning
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS). (Acceptance Rate: 26.1%)
New Orleans, LA, USA. December 10-16, 2023
[ local copy | Arxiv | code ]
Equipping Federated Graph Neural Networks with Structure-aware Group Fairness.
Nan Cui, Xiuling Wang, Hui Wang, Violet Chen, Yue Ning
In Proceedings of the 23rd IEEE International Conference on Data Mining (ICDM). Short Paper. (Acceptance Rate: 19.94%)
Shanghai, China. December 1-4, 2023
[ local copy | Arxiv (long version) | code ]
Healthcare Sustainability: Hospitalization Rate Forecasting with Transfer Learning and Location-Aware News Analysis.
Jing Chen, Germán G. Creamer, Yue Ning, Tal Ben-Zvi
Sustainability (IF: 3.9)
Volume 15, November 2023.
Multi-Label Clinical Time-Series Generation via Conditional GAN.
Chang Lu, Chandan K Reddy, Ping Wang, Dong Nie, Yue Ning
IEEE Transactions on Knowledge and Data Engineering. (IF 8.9)
August 2023.
[ local copy | code ]
Certified Edge Unlearning for Graph Neural Networks.
Kun Wu, Jie Shen, Yue Ning , Ting Wang, Wendy Hui Wang
In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
(KDD). Regular Paper. (Acceptance Rate: 22%)
Long Beach, CA. August 6-10, 2023.
[ local copy | code ]
Forecasting Emerging Pandemics with Transfer Learning and Location-aware News Analysis.
Jing Chen, German Creamer, and Yue Ning
To appear in Proceedings of the 2022 IEEE International Conference on Big Data
(IEEE BigData). Regular Paper. (Acceptance Rate: 19.2%)
Osaka, Japan. December 17-20, 2022.
[ local copy | code ]
Text-enhanced Multi-Granularity Temporal Graph Learning for Event Prediction.
Xiaoxue Han, Yue Ning
In Proceedings of the 22nd IEEE International Conference on Data Mining
(ICDM). Regular Paper. (Acceptance Rate: 9.77%)
Orlando, FL, USA. Nov. 28-Dec. 1, 2022.
[ local copy |
code ]
Causality Enhanced Societal Event Forecasting With Heterogeneous Graph Learning.
Songgaojun Deng, Huzefa Rangwala, Yue Ning
In Proceedings of the 22nd IEEE International Conference on Data Mining
(ICDM). Regular Paper. (Acceptance Rate: 9.77%)
Orlando, FL, USA. Nov. 28-Dec. 1, 2022.
[ local copy |
code ]
Equipping Recommender Systems with Individual Fairness via Second-order Proximity Embedding.
Kun Wu, Jacob Erickson, Wendy Hui Wang and Yue Ning
To appear in Proceedings of the IEEE/ACM International Conference on Social Networks Analysis and Mining
(ASONAM). Short Paper. (Acceptance Rate: 19.6%)
Istanbul, Turkey & Virtual. Nov. 10-13, 2022.
[ local copy |
code ]
Algorithmic Fairness in Computational Medicine.
Jie Xu, Yunyu Xiao, Wendy Hui Wang, Yue Ning, Elizabeth A. Shenkman, Jiang Bian, Fei Wang
eBioMedicine, Part of THE LANCET Discovery Science
(IF: 11.2)
Volume 84, October 2022.
Robust Event Forecasting with Spatiotemporal Confounder Learning.
Songgaojun Deng, Huzefa Rangwala, Yue Ning
In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
(KDD). Full Paper.
Washington DC. August 14-18, 2022. (Acceptance Rate: 14.99%)
[ local copy |
code ]
Weakly-supervised Metric Learning with Cross-Module Communications for the Classification of Anterior Chamber Angle Images.
Jingqi Huang, Yue Ning, Dong Nie, Linan Guan, Xiping Jia.
In Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR). Full Paper.
New Orleans, Louisiana. June 19-24, 2022.
[ local copy |
code ]
Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs.
Chang Lu, Tian Han, Yue Ning.
In Proceedings of the 36th AAAI Conference on Artificial Intelligence
(AAAI). Full Paper.
Online. Feb. 22- March 1, 2022. (Acceptance Rate: 15%)
[ local copy |
Arxiv |
code ]
FairLP: Towards Fair Link Prediction on Social Network Graphs.
Yanying Li, Xiuling Wang, Yue Ning, Hui Wang.
In Proceedings of the 16th International AAAI Conference on Web and Social Media
(ICWSM). Full Paper.
Atlanta, Georgia. June 6-9, 2022.
[ local copy ]
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference.
Jiaxuan Li, Yue Ning.
In Proceedings of the 16th International AAAI Conference on Web and Social Media
(ICWSM). Full Paper.
Atlanta, Georgia. June 6-9, 2022.
[ local copy ]
Recurrent Multi-task Graph Convolutional Networks for COVID-19 Knowledge Graph Link Prediction.
Remington Kim, Yue Ning.
Springer Journal of Communications in Computer and Information Science.
The 5th Annual Smoky Mountains Computational Sciences Data Challenge (SMCDC21).
August 24-26, 2021.
[ local copy ] Recipient of the Best Solution (Novice) Award
Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction.
Chang Lu, Chandan K. Reddy, Yue Ning.
IEEE Transactions on Cybernetics. (IF 11.448)
Pages 1-13, September 21, 2021.
[ local copy |
code ]
Understanding Event Predictions via Contextualized Multilevel Feature Learning.
Songgaojun Deng, Huzefa Rangwala, Yue Ning.
In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM). Research Track.
Online. November 1-5, 2021.
[ local copy |
bibtex |
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Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare.
Chang Lu, Chandan K Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning
In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21). Full Paper.
Online. August 21-26, 2021.
[ local copy |
Arxiv |
code ]
Incorporating Relational Knowledge in Explainable Fake News Detection.
Kun Wu, Xu Yuan, Yue Ning
In Proceedings of 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Full Paper.
Online. May 11-14, 2021.
[ pdf |
media coverage ]
Asynchronous Online Federated Learning for EdgeDevices with Non-IID Data.
Yujing Chen, Yue Ning, Martin Slawski, Huzefa Rangwala
In Proceedings of 2020 IEEE International Conference on Big Data (IEEE BigData). Full Paper.
Online (Atlanta, Georgia, USA). December 10-13th, 2020.
[ pdf |
Arxiv]
Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction.
Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning.
In Proceedings of the 20th ACM International Conference on Information and Knowledge Management (CIKM). Research Track.
Online. October 19-23, 2020. (Acceptance Rate: 21%)
[ pdf |
bibtex |
code ]
Dynamic Knowledge Graph based Multi-Event Forecasting.
Songgaojun Deng, Huzefa Rangwala, Yue Ning.
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Research Track.
Online (San Diego, CA, USA). August 23-27, 2020. (Acceptance Rate: 16.9%)
[ pdf |
bibtex |
code ]
Empirical Analysis of Multi-Task Learning for Reducing Identity Bias in Toxic Comment Detection.
Ameya Vaidya, Feng Mai, Yue Ning.
In Proceedings of the 14th International Conference on Web and Social Media (ICWSM). Full Paper.
Online (Atlanta, Georgia, USA). June 8-11, 2020. (Acceptance Rate: 17%)
[ pdf |
bibtex |
video ]
Federated Multi-task Hierarchical Attention Model for Sensor Analytics.
Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala
In Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN). Full Paper.
Online (Glasgow, Scotland, UK). July 19-24th, 2020,
[ pdf |
Arxiv ]
Fairness of Classification Using Users' Social Relationships in Online Peer-To-Peer Lending.
Yanying Li, Yue Ning, Rong Liu, Ying Wu, Wendy Hui Wang.
In Proceedings of the Second Workshop on Fairness, Accountability, Transparency, Ethics and Society on the Web (FATES). Joint Conference with The Web Conference (WWW). Full Paper.
Online (Taipei, Taiwan). April 20-24, 2020.
[ pdf ]
Learning Dynamic Context Graphs for Predicting Social Events.
Songgaojun Deng, Huzefa Rangwala, Yue Ning.
In Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Research Track - Oral.
Anchorage, Alaska USA. August 4-8, 2019. (Acceptance Rate: 9%)
[ pdf |
bibtex |
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When do Crowds turn Violent? Uncovering Triggers from Media.
Yue Ning, Sathappan Muthiah, Huzefa Rangwala, David Mares and Naren Ramakrishnan.
In Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
Barcelona, Spain. August 28-31, 2018.
[ pdf |
bibtex ]
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting.
Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan.
In Proceedings of the 18th SIAM International Conference on Data Mining (SDM).
San Diego, CA, USA. May 3-5, 2018.
[ pdf |
poster |
bibtex ]
Recipient of SIAM Student Travel Award
Generating Realistic Synthetic Population Datasets.
Hao Wu, Yue Ning, Prithwish Chakraborty, Jilles Vreeken, Nikolaj Tatti, Naren Ramakrishnan.
ACM Transactions on Knowledge Discovery from Data (TKDD). (IF 1.68)
Volume 12 Issue 4, April 2018. DOI: 10.1145/3182383
[
bibtex ]
A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation.
Yue Ning, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan.
In Proceedings of the 11th ACM Conference on Recommender Systems (RecSys).
Como, Italy. Aug. 27-31, 2017.
[ pdf | slides | bibtex ]
Determining Relative Airport Threats from News and Social Media.
Rupinder Paul Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams, Naren Ramakrishnan.
In Proceedings of the 29th Conference on Innovative Applications of Artifical Intelligence (IAAI).
San Francisco, CA, USA. Feb. 4-9, 2017.
[
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bibtex ]
A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events.
Wei Wang, Yue Ning, Huzefa Rangwala, Naren Ramakrishnan.
In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM).
Indianapolis, IN, USA. Oct. 24-28, 2016. (Acceptance Rate: 17.6%)
[
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bibtex
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Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning.
Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan.
In Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Research Track - Oral.
San Francisco, CA, USA. August 13-17, 2016. (Acceptance Rate: 8.9%)
[
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video |
poster |
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Recipient of ACM SIGKDD Student Travel Award
Topical Analysis of Interactions Between News and Social Media.
Ting Hua, Yue Ning, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan.
In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI).
Phoenix, AZ, USA. Feb. 12–17. 2016. (Acceptance Rate: 26%)
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Uncovering News-Twitter Reciprocity via Interaction Patterns.
Yue Ning, Sathappan Muthiah, Ravi Tandon, Naren Ramakrishnan.
In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
Paris, France. Aug. 24-28. 2015. (Acceptance Rate: 18%)
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