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ORCIDYue Ning 0001
Person information
- affiliation: Stevens Institute of Technology, Hoboken, NJ, USA
- affiliation (PhD 2018): Virginia Tech, Arlington, VA, USA
- affiliation (2009-2012): Chinese Academy of Sciences, Institute of Psychology, Beijing, China
Other persons with the same name
- Yue Ning 0002 — Jilin University, ChangChun, China
- Yue Ning 0003
![[0000-0002-5981-2121]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-5981-2121")
— Zhejiang University, Institute of Process Equipment, College of Energy Engineering, Hangzhou, China - Yue Ning 0004 — Xi'an Jiaotong University, Xi'an, China
- Yue Ning 0005 — Ant Group, Hangzhou, China
- Yue Ning 0006 — Hohai University, College of Information Science and Engineering, Changzhou, China
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2020 – today
- 2024
[j4]Chang Lu, Chandan K. Reddy, Ping Wang, Dong Nie, Yue Ning:
Multi-Label Clinical Time-Series Generation via Conditional GAN. IEEE Trans. Knowl. Data Eng. 36(4): 1728-1740 (2024)- [i17]Xiaoxue Han, Zhuo Feng, Yue Ning:
A Topology-aware Graph Coarsening Framework for Continual Graph Learning. CoRR abs/2401.03077 (2024) - [i16]Libo Zhang, Yue Ning:
Large Language Models as Event Forecasters. CoRR abs/2406.10492 (2024) - 2023
- [j3]Chang Lu, Chandan K. Reddy, Yue Ning:
Self-Supervised Graph Learning With Hyperbolic Embedding for Temporal Health Event Prediction. IEEE Trans. Cybern. 53(4): 2124-2136 (2023) - [c35]Nan Cui, Xiuling Wang, Wendy Hui Wang, Violet Chen, Yue Ning:
Equipping Federated Graph Neural Networks with Structure-aware Group Fairness. ICDM 2023: 980-985 - [c34]Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang:
Certified Edge Unlearning for Graph Neural Networks. KDD 2023: 2606-2617 - [c33]Chang Lu, Chandan K. Reddy, Ping Wang, Yue Ning:
Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning. NeurIPS 2023 - [i15]Chang Lu, Chandan K. Reddy, Ping Wang, Yue Ning:
Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning. CoRR abs/2310.09672 (2023) - [i14]Nan Cui, Xiuling Wang, Wendy Hui Wang, Violet Chen, Yue Ning:
Equipping Federated Graph Neural Networks with Structure-aware Group Fairness. CoRR abs/2310.12350 (2023) - 2022
- [j2]K. S. M. Tozammel Hossain, Hrayr Harutyunyan, Yue Ning, Brendan Kennedy, Naren Ramakrishnan, Aram Galstyan:
Identifying geopolitical event precursors using attention-based LSTMs. Frontiers Artif. Intell. 5 (2022) - [c32]Chang Lu, Tian Han, Yue Ning:
Context-Aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs. AAAI 2022: 4567-4574 - [c31]Kun Wu, Jacob Erickson, Wendy Hui Wang, Yue Ning:
Equipping Recommender Systems with Individual Fairness via Second-order Proximity Embedding. ASONAM 2022: 171-175 - [c30]Jing Chen, Germán Creamer, Yue Ning:
Forecasting Emerging Pandemics with Transfer Learning and Location-aware News Analysis. IEEE Big Data 2022: 874-883 - [c29]Jingqi Huang, Yue Ning, Dong Nie, Linan Guan, Xiping Jia:
Weakly-supervised Metric Learning with Cross-Module Communications for the Classification of Anterior Chamber Angle Images. CVPR 2022: 742-752 - [c28]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Causality Enhanced Societal Event Forecasting With Heterogeneous Graph Learning. ICDM 2022: 91-100 - [c27]Xiaoxue Han, Yue Ning:
Text-enhanced Multi-Granularity Temporal Graph Learning for Event Prediction. ICDM 2022: 171-180 - [c26]Jiaxuan Li, Yue Ning:
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference. ICWSM 2022: 607-617 - [c25]Yanying Li, Xiuling Wang, Yue Ning, Hui Wang:
FairLP: Towards Fair Link Prediction on Social Network Graphs. ICWSM 2022: 628-639 - [c24]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Robust Event Forecasting with Spatiotemporal Confounder Learning. KDD 2022: 294-304 - [i13]Chang Lu, Chandan K. Reddy, Ping Wang, Dong Nie, Yue Ning:
Multi-Label Clinical Time-Series Generation via Conditional GAN. CoRR abs/2204.04797 (2022) - [i12]Jiaxuan Li, Yue Ning:
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference. CoRR abs/2204.07010 (2022) - 2021
- [c23]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Understanding Event Predictions via Contextualized Multilevel Feature Learning. CIKM 2021: 342-351 - [c22]Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning:
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare. IJCAI 2021: 3529-3535 - [c21]Kun Wu, Xu Yuan, Yue Ning:
Incorporating Relational Knowledge in Explainable Fake News Detection. PAKDD (3) 2021: 403-415 - [c20]Remington Kim, Yue Ning:
Recurrent Multi-task Graph Convolutional Networks for COVID-19 Knowledge Graph Link Prediction. SMC 2021: 411-419 - [i11]Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning:
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare. CoRR abs/2105.07542 (2021) - [i10]Chang Lu, Chandan K. Reddy, Yue Ning:
Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction. CoRR abs/2106.04751 (2021) - [i9]Chang Lu, Tian Han, Yue Ning:
Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs. CoRR abs/2112.05195 (2021) - [i8]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Causal Knowledge Guided Societal Event Forecasting. CoRR abs/2112.05695 (2021) - [i7]Songgaojun Deng, Yue Ning:
A Survey on Societal Event Forecasting with Deep Learning. CoRR abs/2112.06345 (2021) - 2020
- [c19]Yujing Chen, Yue Ning, Martin Slawski, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices with Non-IID Data. IEEE BigData 2020: 15-24 - [c18]Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning:
Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction. CIKM 2020: 245-254 - [c17]Ameya Vaidya, Feng Mai, Yue Ning:
Empirical Analysis of Multi-Task Learning for Reducing Identity Bias in Toxic Comment Detection. ICWSM 2020: 683-693 - [c16]Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala:
Federated Multi-task Learning with Hierarchical Attention for Sensor Data Analytics. IJCNN 2020: 1-8 - [c15]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Dynamic Knowledge Graph based Multi-Event Forecasting. KDD 2020: 1585-1595 - [c14]Yanying Li, Yue Ning, Rong Liu, Ying Wu, Wendy Hui Wang:
Fairness of Classification Using Users' Social Relationships in Online Peer-To-Peer Lending. WWW (Companion Volume) 2020: 733-742
2010 – 2019
- 2019
- [c13]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Learning Dynamic Context Graphs for Predicting Social Events. KDD 2019: 1007-1016 - [c12]Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu, Huzefa Rangwala:
Spatio-temporal Event Forecasting and Precursor Identification. KDD 2019: 3237-3238 - [i6]Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala:
Federated Multi-task Hierarchical Attention Model for Sensor Analytics. CoRR abs/1905.05142 (2019) - [i5]Ameya Vaidya, Feng Mai, Yue Ning:
Empirical Analysis of Multi-Task Learning for Reducing Model Bias in Toxic Comment Detection. CoRR abs/1909.09758 (2019) - [i4]Yujing Chen, Yue Ning, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices. CoRR abs/1911.02134 (2019) - [i3]Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning:
Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction. CoRR abs/1912.10202 (2019) - 2018
- [b1]Yue Ning:
Modeling Information Precursors for Event Forecasting. Virginia Tech, Blacksburg, VA, USA, 2018 - [j1]Hao Wu, Yue Ning, Prithwish Chakraborty, Jilles Vreeken, Nikolaj Tatti, Naren Ramakrishnan:
Generating Realistic Synthetic Population Datasets. ACM Trans. Knowl. Discov. Data 12(4): 45:1-45:22 (2018) - [c11]Yue Ning, Sathappan Muthiah, Naren Ramakrishnan, Huzefa Rangwala, David Mares:
When do Crowds Turn Violent? Uncovering Triggers from Media. ASONAM 2018: 77-82 - [c10]Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan:
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. SDM 2018: 99-107 - 2017
- [c9]Rupinder Paul Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik R. Smith, Christopher Adams, Naren Ramakrishnan:
Determining Relative Airport Threats from News and Social Media. AAAI 2017: 4701-4707 - [c8]Yue Ning, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan:
A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. RecSys 2017: 23-31 - 2016
- [c7]Ting Hua, Yue Ning, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Topical Analysis of Interactions Between News and Social Media. AAAI 2016: 2964-2971 - [c6]Wei Wang, Yue Ning, Huzefa Rangwala, Naren Ramakrishnan:
A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events. CIKM 2016: 509-518 - [c5]Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan:
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. KDD 2016: 1095-1104 - [i2]Hao Wu, Yue Ning, Prithwish Chakraborty, Jilles Vreeken, Nikolaj Tatti, Naren Ramakrishnan:
Generating Realistic Synthetic Population Datasets. CoRR abs/1602.06844 (2016) - [i1]Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan:
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. CoRR abs/1602.08033 (2016) - 2015
- [c4]Yue Ning, Sathappan Muthiah, Ravi Tandon, Naren Ramakrishnan:
Uncovering News-Twitter Reciprocity via Interaction Patterns. ASONAM 2015: 1-8 - 2012
- [c3]Dong Nie, Yue Ning, Tingshao Zhu:
Predicting Mental Health Status in the Context of Web Browsing. Web Intelligence/IAT Workshops 2012: 185-189 - [c2]Shuotian Bai, Yue Ning, Sha Yuan, Tingshao Zhu:
Predicting Reader's Emotion on Chinese Web News Articles. ICPCA/SWS 2012: 16-27 - 2011
- [c1]Tingshao Zhu, Ang Li, Yue Ning, Zengda Guan:
Predicting Mental Health Status Based on Web Usage Behavior. AMT 2011: 186-194
Coauthor Index
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last updated on 2024-08-14 23:19 CEST by the dblp team
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