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ORCIDJingrui He
何京芮
Person information
- affiliation: University of Illinois at Urbana-Champaign, IL, USA
- affiliation: Arizona State University, AZ, USA
- affiliation (Ph.D., 2010): Carnegie Mellon University, PA, USA
- affiliation (former): Tsinghua University, China
- unicode name: 何京芮
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2020 – today
- 2024
[j32]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)- [j31]Dawei Zhou, Jingrui He:
Rare Category Analysis for Complex Data: A Review. ACM Comput. Surv. 56(5): 123:1-123:35 (2024) - [c150]Wenxuan Bao, Jun Wu, Jingrui He:
BOBA: Byzantine-Robust Federated Learning with Label Skewness. AISTATS 2024: 892-900 - [c149]Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He:
Fairgen: Towards Fair Graph Generation. ICDE 2024: 2285-2297 - [c148]Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He:
Neural Active Learning Beyond Bandits. ICLR 2024 - [c147]Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee:
Contextual Bandits with Online Neural Regression. ICLR 2024 - [c146]Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long:
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections. ICLR 2024 - [c145]Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang:
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. ICLR 2024 - [c144]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 - [c143]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 - [c142]Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He:
Meta Clustering of Neural Bandits. KDD 2024: 95-106 - [c141]Jun Wu, Jingrui He, Hanghang Tong:
Distributional Network of Networks for Modeling Data Heterogeneity. KDD 2024: 3379-3390 - [c140]Lecheng Zheng, Baoyu Jing, Zihao Li, Hanghang Tong, Jingrui He:
Heterogeneous Contrastive Learning for Foundation Models and Beyond. KDD 2024: 6666-6676 - [c139]Zihao Li, Yuyi Ao, Jingrui He:
SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval. SIGIR 2024: 2629-2634 - [c138]Haonan Wang, Ziwei Wu, Jingrui He:
FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes. WSDM 2024: 721-730 - [c137]Yikun Ban, Yunzhe Qi, Jingrui He:
Neural Contextual Bandits for Personalized Recommendation. WWW (Companion Volume) 2024: 1246-1249 - [c136]Jingrui He, Jian Kang, Fatemeh Nargesian, Haohui Wang, An Zhang, Dawei Zhou:
TrustLOG: The Second Workshop on Trustworthy Learning on Graphs. WWW (Companion Volume) 2024: 1785-1788 - [c135]Xinrui He, Shuo Liu, Jacky Keung, Jingrui He:
Co-clustering for Federated Recommender System. WWW 2024: 3821-3832 - [c134]Lecheng Zheng, Zhengzhang Chen, Jingrui He, Haifeng Chen:
MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems. WWW 2024: 4107-4116 - [i60]Lecheng Zheng, Zhengzhang Chen, Jingrui He, Haifeng Chen:
Multi-modal Causal Structure Learning and Root Cause Analysis. CoRR abs/2402.02357 (2024) - [i59]Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang:
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. CoRR abs/2403.10667 (2024) - [i58]Baoyu Jing, Yansen Wang, Guoxin Sui, Jing Hong, Jingrui He, Yuqing Yang, Dongsheng Li, Kan Ren:
Automated Contrastive Learning Strategy Search for Time Series. CoRR abs/2403.12641 (2024) - [i57]Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long:
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections. CoRR abs/2403.16030 (2024) - [i56]Lecheng Zheng, Baoyu Jing, Zihao Li, Hanghang Tong, Jingrui He:
Heterogeneous Contrastive Learning for Foundation Models and Beyond. CoRR abs/2404.00225 (2024) - [i55]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) - [i54]Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He:
Neural Active Learning Beyond Bandits. CoRR abs/2404.12522 (2024) - [i53]Zihao Li, Yuyi Ao, Jingrui He:
SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval. CoRR abs/2404.19130 (2024) - [i52]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) - [i51]Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He:
Meta Clustering of Neural Bandits. CoRR abs/2408.05586 (2024) - 2023
- [j30]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) - [j29]Jun Wu, Jingrui He:
A Unified Framework for Adversarial Attacks on Multi-Source Domain Adaptation. IEEE Trans. Knowl. Data Eng. 35(11): 11039-11050 (2023) - [c133]Jun Wu, Jingrui He, Elizabeth A. Ainsworth:
Non-IID Transfer Learning on Graphs. AAAI 2023: 10342-10350 - [c132]Xinrui He, Tianxin Wei, Jingrui He:
Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning. CIKM 2023: 709-719 - [c131]Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He:
Optimizing the Collaboration Structure in Cross-Silo Federated Learning. ICML 2023: 1718-1736 - [c130]Tianxin Wei, Zeming Guo, Yifan Chen, Jingrui He:
NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning. ICML 2023: 36821-36838 - [c129]Yunzhe Qi, Yikun Ban, Jingrui He:
Graph Neural Bandits. KDD 2023: 1920-1931 - [c128]Jun Wu, Wenxuan Bao, Elizabeth A. Ainsworth, Jingrui He:
Personalized Federated Learning with Parameter Propagation. KDD 2023: 2594-2605 - [c127]Jun Wu, Jingrui He:
Trustworthy Transfer Learning: Transferability and Trustworthiness. KDD 2023: 5829-5830 - [c126]Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik:
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD 2023: 5870-5871 - [c125]Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He:
Adaptive Test-Time Personalization for Federated Learning. NeurIPS 2023 - [c124]Yunzhe Qi, Yikun Ban, Tianxin Wei, Jiaru Zou, Huaxiu Yao, Jingrui He:
Meta-Learning with Neural Bandit Scheduler. NeurIPS 2023 - [c123]Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He:
Graph-Structured Gaussian Processes for Transferable Graph Learning. NeurIPS 2023 - [c122]Lecheng Zheng, Yada Zhu, Jingrui He:
Fairness-aware Multi-view Clustering. SDM 2023: 856-864 - [c121]Dongqi Fu, Zhe Xu, Hanghang Tong, Jingrui He:
Natural and Artificial Dynamics in GNNs: A Tutorial. WSDM 2023: 1252-1255 - [c120]Zihao Li, Dongqi Fu, Jingrui He:
Everything Evolves in Personalized PageRank. WWW 2023: 3342-3352 - [c119]Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, Jingrui He:
Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs. WWW 2023: 3755-3765 - [e3]Jingrui He, Themis Palpanas, Xiaohua Hu, Alfredo Cuzzocrea, Dejing Dou, Dominik Slezak, Wei Wang, Aleksandra Gruca, Jerry Chun-Wei Lin, Rakesh Agrawal:
IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, December 15-18, 2023. IEEE 2023, ISBN 979-8-3503-2445-7 [contents] - [i50]Lecheng Zheng, Yada Zhu, Jingrui He:
Fairness-aware Multi-view Clustering. CoRR abs/2302.05788 (2023) - [i49]Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He:
FairGen: Towards Fair Graph Generation. CoRR abs/2303.17743 (2023) - [i48]Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He:
Neural Exploitation and Exploration of Contextual Bandits. CoRR abs/2305.03784 (2023) - [i47]Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He:
Optimizing the Collaboration Structure in Cross-Silo Federated Learning. CoRR abs/2306.06508 (2023) - [i46]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) - [i45]Tianxin Wei, Zeming Guo, Yifan Chen, Jingrui He:
NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning. CoRR abs/2307.08941 (2023) - [i44]Yunzhe Qi, Yikun Ban, Jingrui He:
Graph Neural Bandits. CoRR abs/2308.10808 (2023) - [i43]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) - [i42]Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He:
Adaptive Test-Time Personalization for Federated Learning. CoRR abs/2310.18816 (2023) - [i41]Xinrui He, Tianxin Wei, Jingrui He:
Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning. CoRR abs/2311.16334 (2023) - [i40]Haoyang Liu, Tiancheng Xing, Luwei Li, Vibhu Dalal, Jingrui He, Haohan Wang:
Dataset Distillation via the Wasserstein Metric. CoRR abs/2311.18531 (2023) - [i39]Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee:
Contextual Bandits with Online Neural Regression. CoRR abs/2312.07145 (2023) - [i38]Yikun Ban, Yunzhe Qi, Jingrui He:
Neural Contextual Bandits for Personalized Recommendation. CoRR abs/2312.14037 (2023) - 2022
- [j28]Dongming Han, Jiacheng Pan, Rusheng Pan, Dawei Zhou, Nan Cao, Jingrui He, Mingliang Xu, Wei Chen:
iNet: visual analysis of irregular transition in multivariate dynamic networks. Frontiers Comput. Sci. 16(2): 162701 (2022) - [j27]Dongqi Fu, Jingrui He:
Natural and Artificial Dynamics in Graphs: Concept, Progress, and Future. Frontiers Big Data 5 (2022) - [j26]Jun Wu, Jingrui He:
Dynamic transfer learning with progressive meta-task scheduler. Frontiers Big Data 5 (2022) - [j25]Yang Shi, Yuyin Liu, Hanghang Tong, Jingrui He, Gang Yan, Nan Cao:
Visual Analytics of Anomalous User Behaviors: A Survey. IEEE Trans. Big Data 8(2): 377-396 (2022) - [c118]Jun Wu, Hanghang Tong, Elizabeth A. Ainsworth, Jingrui He:
Adaptive Knowledge Transfer on Evolving Domains. IEEE Big Data 2022: 1389-1394 - [c117]Dongqi Fu, Jingrui He:
DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data. IEEE Big Data 2022: 5269-5277 - [c116]Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He:
MentorGNN: Deriving Curriculum for Pre-Training GNNs. CIKM 2022: 2721-2731 - [c115]Yao Zhou, Jun Wu, Haixun Wang, Jingrui He:
Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning. CIKM 2022: 2753-2762 - [c114]Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, Jingrui He:
DISCO: Comprehensive and Explainable Disinformation Detection. CIKM 2022: 4848-4852 - [c113]Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou:
TrustLOG: The First Workshop on Trustworthy Learning on Graphs. CIKM 2022: 5169-5170 - [c112]Ziwei Wu, Jingrui He:
Fairness-aware Model-agnostic Positive and Unlabeled Learning. FAccT 2022: 1698-1708 - [c111]Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He:
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits. ICLR 2022 - [c110]Jun Wu, Jingrui He:
A Unified Meta-Learning Framework for Dynamic Transfer Learning. IJCAI 2022: 3573-3579 - [c109]Dongqi Fu, Liri Fang, Ross Maciejewski, Vetle I. Torvik, Jingrui He:
Meta-Learned Metrics over Multi-Evolution Temporal Graphs. KDD 2022: 367-377 - [c108]Yunzhe Qi, Yikun Ban, Jingrui He:
Neural Bandit with Arm Group Graph. KDD 2022: 1379-1389 - [c107]Tianxin Wei, Jingrui He:
Comprehensive Fair Meta-learned Recommender System. KDD 2022: 1989-1999 - [c106]Jun Wu, Jingrui He:
Domain Adaptation with Dynamic Open-Set Targets. KDD 2022: 2039-2049 - [c105]Lecheng Zheng, Jinjun Xiong, Yada Zhu, Jingrui He:
Contrastive Learning with Complex Heterogeneity. KDD 2022: 2594-2604 - [c104]Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, Elizabeth A. Ainsworth:
Distribution-Informed Neural Networks for Domain Adaptation Regression. NeurIPS 2022 - [c103]Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He:
Improved Algorithms for Neural Active Learning. NeurIPS 2022 - [c102]Haonan Wang, Wei Huang, Ziwei Wu, Hanghang Tong, Andrew Margenot, Jingrui He:
Deep Active Learning by Leveraging Training Dynamics. NeurIPS 2022 - [c101]Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang:
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative. NeurIPS 2022 - [i37]Jun Wu, Elizabeth A. Ainsworth, Sheng Wang, Kaiyu Guan, Jingrui He:
Adaptive Transfer Learning for Plant Phenotyping. CoRR abs/2201.05261 (2022) - [i36]Haonan Wang, Ziwei Wu, Jingrui He:
Training Fair Deep Neural Networks by Balancing Influence. CoRR abs/2201.05759 (2022) - [i35]Yikun Ban, Yunzhe Qi, Tianxin Wei, Jingrui He:
Neural Collaborative Filtering Bandits via Meta Learning. CoRR abs/2201.13395 (2022) - [i34]Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, Jingrui He:
DISCO: Comprehensive and Explainable Disinformation Detection. CoRR abs/2203.04928 (2022) - [i33]Yunzhe Qi, Yikun Ban, Jingrui He:
Neural Bandit with Arm Group Graph. CoRR abs/2206.03644 (2022) - [i32]Tianxin Wei, Jingrui He:
Comprehensive Fair Meta-learned Recommender System. CoRR abs/2206.04789 (2022) - [i31]Ziwei Wu, Jingrui He:
Fairness-aware Model-agnostic Positive and Unlabeled Learning. CoRR abs/2206.09346 (2022) - [i30]Dongqi Fu, Jingrui He, Hanghang Tong, Ross Maciejewski:
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning. CoRR abs/2207.00048 (2022) - [i29]Jun Wu, Jingrui He:
A Unified Meta-Learning Framework for Dynamic Transfer Learning. CoRR abs/2207.01784 (2022) - [i28]Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He:
MentorGNN: Deriving Curriculum for Pre-Training GNNs. CoRR abs/2208.09905 (2022) - [i27]Wenxuan Bao, Jingrui He:
BOBA: Byzantine-Robust Federated Learning with Label Skewness. CoRR abs/2208.12932 (2022) - [i26]Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He:
Improved Algorithms for Neural Active Learning. CoRR abs/2210.00423 (2022) - [i25]Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang:
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative. CoRR abs/2210.03801 (2022) - [i24]Jun Wu, Jingrui He, Elizabeth A. Ainsworth:
Non-IID Transfer Learning on Graphs. CoRR abs/2212.08174 (2022) - 2021
- [j24]Xu Liu, Congzhe Su, Amey Barapatre, Xiaoting Zhao, Diane Hu, Chu-Cheng Hsieh, Jingrui He:
Interpretable Attribute-based Action-aware Bandits for Within-Session Personalization in E-commerce. IEEE Data Eng. Bull. 44(2): 65-80 (2021) - [j23]Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong, Hasan Davulcu, Jingrui He:
High-Order Structure Exploration on Massive Graphs: A Local Graph Clustering Perspective. ACM Trans. Knowl. Discov. Data 15(2): 18:1-18:26 (2021) - [j22]Yuxin Ma, Arlen Fan, Jingrui He, Arun Reddy Nelakurthi, Ross Maciejewski:
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes. IEEE Trans. Vis. Comput. Graph. 27(2): 1385-1395 (2021) - [c100]Jianbo Li, Lecheng Zheng, Yada Zhu, Jingrui He:
Outlier Impact Characterization for Time Series Data. AAAI 2021: 11595-11603 - [c99]Yikun Ban, Jingrui He, Curtiss B. Cook:
Multi-facet Contextual Bandits: A Neural Network Perspective. KDD 2021: 35-45 - [c98]Jun Wu, Jingrui He:
Indirect Invisible Poisoning Attacks on Domain Adaptation. KDD 2021: 1852-1862 - [c97]Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He:
PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network. KDD 2021: 2409-2419 - [c96]Dongqi Fu, Jingrui He:
SDG: A Simplified and Dynamic Graph Neural Network. SIGIR 2021: 2273-2277 - [c95]Haonan Wang, Chang Zhou, Carl Yang, Hongxia Yang, Jingrui He:
Controllable Gradient Item Retrieval. WWW 2021: 768-777 - [c94]Lecheng Zheng, Yu Cheng, Hongxia Yang, Nan Cao, Jingrui He:
Deep Co-Attention Network for Multi-View Subspace Learning. WWW 2021: 1528-1539 - [c93]Yikun Ban, Jingrui He:
Local Clustering in Contextual Multi-Armed Bandits. WWW 2021: 2335-2346 - [i23]Lecheng Zheng, Yu Cheng, Hongxia Yang, Nan Cao, Jingrui He:
Deep Co-Attention Network for Multi-View Subspace Learning. CoRR abs/2102.07751 (2021) - [i22]Yikun Ban, Jingrui He:
Local Clustering in Contextual Multi-Armed Bandits. CoRR abs/2103.00063 (2021) - [i21]Lecheng Zheng, Yada Zhu, Jingrui He, Jinjun Xiong:
Heterogeneous Contrastive Learning. CoRR abs/2105.09401 (2021) - [i20]Haonan Wang, Chang Zhou, Carl Yang, Hongxia Yang, Jingrui He:
Controllable Gradient Item Retrieval. CoRR abs/2106.00062 (2021) - [i19]Yikun Ban, Jingrui He, Curtiss B. Cook:
Multi-facet Contextual Bandits: A Neural Network Perspective. CoRR abs/2106.03039 (2021) - [i18]Dongqi Fu, Jingrui He:
DPPIN: A Biological Dataset of Dynamic Protein-Protein Interaction Networks. CoRR abs/2107.02168 (2021) - [i17]Yikun Ban, Jingrui He:
Convolutional Neural Bandit: Provable Algorithm for Visual-aware Advertising. CoRR abs/2107.07438 (2021) - [i16]Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He:
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits. CoRR abs/2110.03177 (2021) - [i15]Haonan Wang, Wei Huang, Andrew Margenot, Hanghang Tong, Jingrui He:
Deep Active Learning by Leveraging Training Dynamics. CoRR abs/2110.08611 (2021) - [i14]Lecheng Zheng, Dongqi Fu, Jingrui He:
Tackling Oversmoothing of GNNs with Contrastive Learning. CoRR abs/2110.13798 (2021) - [i13]Yao Zhou, Haonan Wang, Jingrui He, Haixun Wang:
From Intrinsic to Counterfactual: On the Explainability of Contextualized Recommender Systems. CoRR abs/2110.14844 (2021) - 2020
- [j21]Jiacheng Pan, Dongming Han, Fangzhou Guo, Dawei Zhou, Nan Cao, Jingrui He, Mingliang Xu, Wei Chen:
RCAnalyzer: visual analytics of rare categories in dynamic networks. Frontiers Inf. Technol. Electron. Eng. 21(4): 491-506 (2020) - [j20]Pei Yang, Qi Tan, Jingrui He:
Complex heterogeneity learning: A theoretical and empirical study. Pattern Recognit. 107: 107519 (2020) - [c92]Zhining Liu, Dawei Zhou, Yada Zhu, Jinjie Gu, Jingrui He:
Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk. AAAI 2020: 4973-4980 - [c91]Shane Roach, Connie Ni, Alexei Kopylov, Tsai-Ching Lu,