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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) - [c151]Wenxuan Bao, Jun Wu, Jingrui He:
BOBA: Byzantine-Robust Federated Learning with Label Skewness. AISTATS 2024: 892-900 - [c150]Baoyu Jing, Yansen Wang, Guoxin Sui, Jing Hong, Jingrui He, Yuqing Yang, Dongsheng Li, Kan Ren:
Automated Contrastive Learning Strategy Search for Time Series. CIKM 2024: 4612-4620 - [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 - [i63]Lecheng Zheng, Zhengzhang Chen, Jingrui He, Haifeng Chen:
Multi-modal Causal Structure Learning and Root Cause Analysis. CoRR abs/2402.02357 (2024) - [i62]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) - [i61]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) - [i60]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) - [i59]Lecheng Zheng, Baoyu Jing, Zihao Li, Hanghang Tong, Jingrui He:
Heterogeneous Contrastive Learning for Foundation Models and Beyond. CoRR abs/2404.00225 (2024) - [i58]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) - [i57]Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He:
Neural Active Learning Beyond Bandits. CoRR abs/2404.12522 (2024) - [i56]Zihao Li, Yuyi Ao, Jingrui He:
SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval. CoRR abs/2404.19130 (2024) - [i55]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) - [i54]Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He:
Meta Clustering of Neural Bandits. CoRR abs/2408.05586 (2024) - [i53]Lecheng Zheng, John R. Birge, Yifang Zhang, Jingrui He:
Towards Multi-view Graph Anomaly Detection with Similarity-Guided Contrastive Clustering. CoRR abs/2409.09770 (2024) - [i52]Ziwei Wu, Lecheng Zheng, Yuancheng Yu, Ruizhong Qiu, John R. Birge, Jingrui He:
Fair Anomaly Detection For Imbalanced Groups. CoRR abs/2409.10951 (2024) - [i51]Wenxuan Bao, Zhichen Zeng, Zhining Liu, Hanghang Tong, Jingrui He:
AdaRC: Mitigating Graph Structure Shifts during Test-Time. CoRR abs/2410.06976 (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, Jiejun Xu, Si Zhang, Boxin Du, Dawei Zhou, Jun Wu, Lihui Liu, Yuchen Yan, Jingrui He, Hanghang Tong:
CANON: Complex Analytics of Network of Networks for Modeling Adversarial Activities. IEEE BigData 2020: 1634-1643 - [c90]Dongqi Fu, Zhe Xu, Bo Li, Hanghang Tong, Jingrui He:
A View-Adversarial Framework for Multi-View Network Embedding. CIKM 2020: 2025-2028 - [c89]Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong:
InFoRM: Individual Fairness on Graph Mining. KDD 2020: 379-389 - [c88]Dongqi Fu, Dawei Zhou, Jingrui He:
Local Motif Clustering on Time-Evolving Graphs. KDD 2020: 390-400 - [c87]Dawei Zhou, Lecheng Zheng, Jiawei Han, Jingrui He:
A Data-Driven Graph Generative Model for Temporal Interaction Networks. KDD 2020: 401-411 - [c86]Yikun Ban, Jingrui He:
Generic Outlier Detection in Multi-Armed Bandit. KDD 2020: 913-923 - [c85]Yao Zhou, Arun Reddy Nelakurthi, Ross Maciejewski, Wei Fan, Jingrui He:
Crowd Teaching with Imperfect Labels. WWW 2020: 110-121 - [c84]Dawei Zhou, Lecheng Zheng, Yada Zhu, Jianbo Li, Jingrui He:
Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting. WWW 2020: 2230-2240 - [i12]Jun Wu, Jingrui He:
Continuous Transfer Learning with Label-informed Distribution Alignment. CoRR abs/2006.03230 (2020) - [i11]Yikun Ban, Jingrui He:
Generic Outlier Detection in Multi-Armed Bandit. CoRR abs/2007.07293 (2020) - [i10]Yuxin Ma, Arlen Fan, Jingrui He, Arun Reddy Nelakurthi, Ross Maciejewski:
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes. CoRR abs/2009.06876 (2020) - [i9]Yao Zhou, Jun Wu, Jingrui He:
Robust Decentralized Learning for Neural Networks. CoRR abs/2009.09026 (2020) - [i8]Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He:
GAN-based Recommendation with Positive-Unlabeled Sampling. CoRR abs/2012.06901 (2020)
2010 – 2019
- 2019
- [j19]Dawei Zhou, Lecheng Zheng, Jiejun Xu, Jingrui He:
Misc-GAN: A Multi-scale Generative Model for Graphs. Frontiers Big Data 2: 3 (2019) - [j18]Chieh-Yang Huang, Hanghang Tong, Jingrui He, Ross Maciejewski:
Location Prediction for Tweets. Frontiers Big Data 2: 5 (2019) - [j17]Yao Zhou, Lei Ying, Jingrui He:
Multi-task Crowdsourcing via an Optimization Framework. ACM Trans. Knowl. Discov. Data 13(3): 27:1-27:26 (2019) - [c83]Jun Wu, Jingrui He:
Scalable Manifold-Regularized Attributed Network Embedding via Maximum Mean Discrepancy. CIKM 2019: 2101-2104 - [c82]Zhining Liu, Dawei Zhou, Jingrui He:
Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention Networks. CIKM 2019: 2137-2140 - [c81]Xu Liu, Jingrui He, Sam Duddy, Liz O'Sullivan:
Convolution-Consistent Collective Matrix Completion. CIKM 2019: 2209-2212 - [c80]Pei Yang, Qi Tan, Jieping Ye, Hanghang Tong, Jingrui He:
Deep Multi-Task Learning with Adversarial-and-Cooperative Nets. IJCAI 2019: 4078-4084 - [c79]Jun Wu, Jingrui He, Jiejun Xu:
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. KDD 2019: 406-415 - [c78]Pei Yang, Qi Tan, Hanghang Tong, Jingrui He:
Task-Adversarial Co-Generative Nets. KDD 2019: 1596-1604 - [c77]Dawei Zhou, Jingrui He:
Gold Panning from the Mess: Rare Category Exploration, Exposition, Representation, and Interpretation. KDD 2019: 3213-3214 - [c76]Yao Zhou, Fenglong Ma, Jing Gao, Jingrui He:
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. KDD 2019: 3231-3232 - [c75]Lecheng Zheng, Yu Cheng, Jingrui He:
Deep Multimodality Model for Multi-task Multi-view Learning. SDM 2019: 10-18 - [i7]Lecheng Zheng, Yu Cheng, Jingrui He:
Deep Multimodality Model for Multi-task Multi-view Learning. CoRR abs/1901.08723 (2019) - [i6]Yang Shi, Yuyin Liu, Hanghang Tong, Jingrui He, Gang Yan, Nan Cao:
Visual Analytics of Anomalous User Behaviors: A Survey. CoRR abs/1905.06720 (2019) - [i5]Jun Wu, Jingrui He, Jiejun Xu:
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. CoRR abs/1906.02319 (2019) - [i4]Yikun Ban, Yuchen Zhou, Jingrui He, Xu Cheng, Jiangfang Yi:
Coalesced TLB to Exploit Diverse Contiguity of Memory Mapping. CoRR abs/1908.08774 (2019) - 2018
- [j16]Shuo Feng, Derong Shen, Tiezheng Nie, Yue Kou, Jingrui He, Ge Yu:
Inferring Anchor Links Based on Social Network Structure. IEEE Access 6: 17340-17353 (2018) - [j15]Pei Yang, Qi Tan, Yada Zhu, Jingrui He:
Heterogeneous representation learning with separable structured sparsity regularization. Knowl. Inf. Syst. 55(3): 671-694 (2018) - [j14]Qi Tan, Pei Yang, Jingrui He:
Feature co-shrinking for co-clustering. Pattern Recognit. 77: 12-19 (2018) - [j13]Pei Yang, Qi Tan, Jingrui He:
Function-on-Function Regression with Mode-Sparsity Regularization. ACM Trans. Knowl. Discov. Data 12(3): 36:1-36:23 (2018) - [j12]Hanfei Lin, Siyuan Gao, David Gotz, Fan Du, Jingrui He, Nan Cao:
RCLens: Interactive Rare Category Exploration and Identification. IEEE Trans. Vis. Comput. Graph. 24(7): 2223-2237 (2018) - [c74]Arun Reddy Nelakurthi, Ross Maciejewski, Jingrui He:
Source Free Domain Adaptation Using an Off-the-Shelf Classifier. IEEE BigData 2018: 140-145 - [c73]Jun Wu, Jingrui He, Yongming Liu:
ImVerde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation. IEEE BigData 2018: 871-880 - [c72]Dawei Zhou, Jingrui He, Hasan Davulcu, Ross Maciejewski:
Motif-Preserving Dynamic Local Graph Cut. IEEE BigData 2018: 1156-1161 - [c71]Yada Zhu, Jianbo Li, Jingrui He, Brian Leo Quanz, Ajay A. Deshpande:
A Local Algorithm for Product Return Prediction in E-Commerce. IJCAI 2018: 3718-3724 - [c70]Jianbo Li, Jingrui He, Yada Zhu:
E-tail Product Return Prediction via Hypergraph-based Local Graph Cut. KDD 2018: 519-527 - [c69]Dawei Zhou, Jingrui He, Hongxia Yang, Wei Fan:
SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization. KDD 2018: 2807-2816 - [c68]Yao Zhou, Arun Reddy Nelakurthi, Jingrui He:
Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners. KDD 2018: 2817-2826 - [c67]Pengfei Jiang, Weina Wang, Yao Zhou, Jingrui He, Lei Ying:
A Winners-Take-All Incentive Mechanism for Crowd-Powered Systems. NetEcon@SIGMETRICS 2018: 3:1-3:6 - [c66]Jiejun Xu, Hanghang Tong, Tsai-Ching Lu, Jingrui He, Nadya Bliss:
GTA3 2018: Workshop on Graph Techniques for Adversarial Activity Analytics. WSDM 2018: 803 - [e2]Naoki Abe, Huan Liu, Calton Pu, Xiaohua Hu, Nesreen K. Ahmed, Mu Qiao, Yang Song, Donald Kossmann, Bing Liu, Kisung Lee, Jiliang Tang, Jingrui He, Jeffrey S. Saltz:
IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018. IEEE 2018, ISBN 978-1-5386-5035-6 [contents] - [r2]Yada Zhu, Jingrui He:
Social Phishing. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i3]Yao Zhou, Arun Reddy Nelakurthi, Jingrui He:
Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners. CoRR abs/1804.06481 (2018) - [i2]Jun Wu, Jingrui He, Yongming Liu:
ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data. CoRR abs/1804.09222 (2018) - [i1]Yao Zhou, Jingrui He:
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. CoRR abs/1806.09018 (2018) - 2017
- [j11]Dawei Zhou, Arun Karthikeyan, Kangyang Wang, Nan Cao, Jingrui He:
Discovering rare categories from graph streams. Data Min. Knowl. Discov. 31(2): 400-423 (2017) - [j10]Chen Chen, Jingrui He, Nadya Bliss, Hanghang Tong:
Towards Optimal Connectivity on Multi-Layered Networks. IEEE Trans. Knowl. Data Eng. 29(10): 2332-2346 (2017) - [c65]Arun Reddy Nelakurthi, Jingrui He:
Finding Cut from the Same Cloth: Cross Network Link Recommendation via Joint Matrix Factorization. AAAI 2017: 1467-1473 - [c64]Jianbo Li, Jingrui He, Yada Zhu:
HiMuV: Hierarchical Framework for Modeling Multi-modality Multi-resolution Data. ICDM 2017: 267-276 - [c63]Yao Zhou, Jingrui He:
A Randomized Approach for Crowdsourcing in the Presence of Multiple Views. ICDM 2017: 685-694 - [c62]Jingrui He:
Learning from Data Heterogeneity: Algorithms and Applications. IJCAI 2017: 5126-5130 - [c61]Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong, Hasan Davulcu, Jingrui He:
A Local Algorithm for Structure-Preserving Graph Cut. KDD 2017: 655-664 - [c60]Pei Yang, Qi Tan, Jingrui He:
Multi-task Function-on-function Regression with Co-grouping Structured Sparsity. KDD 2017: 1255-1264 - [c59]Hongxia Yang, Yada Zhu, Jingrui He:
Local Algorithm for User Action Prediction Towards Display Ads. KDD 2017: 2091-2099 - [c58]Arun Reddy Nelakurthi, Hanghang Tong, Ross Maciejewski, Nadya Bliss, Jingrui He:
User-guided Cross-domain Sentiment Classification. SDM 2017: 471-479 - [c57]Si Zhang, Dawei Zhou, Mehmet Yigit Yildirim, Scott Alcorn, Jingrui He, Hasan Davulcu, Hanghang Tong:
HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection. SDM 2017: 570-578 - [c56]Yao Zhou, Lei Ying, Jingrui He:
MultiC2: an Optimization Framework for Learning from Task and Worker Dual Heterogeneity. SDM 2017: 579-587 - [c55]Yada Zhu, Jianbo Li, Jingrui He:
Learning from Multi-Modality Multi-Resolution Data: an Optimization Approach. SDM 2017: 714-722 - 2016
- [j9]Pei Yang, Hongxia Yang, Haoda Fu, Dawei Zhou, Jieping Ye, Theodoros Lappas, Jingrui He:
Jointly Modeling Label and Feature Heterogeneity in Medical Informatics. ACM Trans. Knowl. Discov. Data 10(4): 39:1-39:25 (2016) - [j8]Yada Zhu, Jingrui He:
Co-Clustering Structural Temporal Data with Applications to Semiconductor Manufacturing. ACM Trans. Knowl. Discov. Data 10(4): 43:1-43:18 (2016) - [j7]Pei Yang, Hasan Davulcu, Yada Zhu, Jingrui He:
A Generalized Hierarchical Multi-Latent Space Model for Heterogeneous Learning. IEEE Trans. Knowl. Data Eng. 28(12): 3154-3168 (2016) - [c54]Pei Yang, Jingrui He:
Heterogeneous Representation Learning with Structured Sparsity Regularization. ICDM 2016: 539-548 - [c53]Dawei Zhou, Jingrui He, Yu Cao, Jae-sun Seo:
Bi-Level Rare Temporal Pattern Detection. ICDM 2016: 719-728 - [c52]Pei Yang, Jingrui He:
Functional Regression with Mode-Sparsity Constraint. ICDM 2016: 1311-1316 - [c51]Yao Zhou, Jingrui He:
Crowdsourcing via Tensor Augmentation and Completion. IJCAI 2016: 2435-2441 - 2015
- [j6]Yada Zhu, Jingrui He, Richard D. Lawrence:
A general framework for predictive tensor modeling with domain knowledge. Data Min. Knowl. Discov. 29(6): 1709-1732 (2015) - [c50]Deqing Yang, Jingrui He, Huazheng Qin, Yanghua Xiao, Wei Wang:
A Graph-based Recommendation across Heterogeneous Domains. CIKM 2015: 463-472 - [c49]Chen Chen, Jingrui He, Nadya Bliss, Hanghang Tong:
On the Connectivity of Multi-layered Networks: Models, Measures and Optimal Control. ICDM 2015: 715-720 - [c48]Pei Yang, Jingrui He:
A Graph-Based Hybrid Framework for Modeling Complex Heterogeneity. ICDM 2015: 1081-1086 - [c47]Dawei Zhou, Kangyang Wang, Nan Cao, Jingrui He:
Rare Category Detection on Time-Evolving Graphs. ICDM 2015: 1135-1140 - [c46]Chenhao Xie, Deqing Yang, Jingrui He, Yanghua Xiao:
Cross-Site Virtual Social Network Construction. ICDM Workshops 2015: 1660-1663 - [c45]Dawei Zhou, Jingrui He, K. Selçuk Candan, Hasan Davulcu:
MUVIR: Multi-View Rare Category Detection. IJCAI 2015: 4098-4104 - [c44]Pei Yang, Jingrui He:
Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning. KDD 2015: 1375-1384 - [c43]Yada Zhu, Hongxia Yang, Jingrui He:
Co-Clustering based Dual Prediction for Cargo Pricing Optimization. KDD 2015: 1583-1592 - [c42]David C. Kale, Marjan Ghazvininejad, Anil Ramakrishna, Jingrui He, Yan Liu:
Hierarchical Active Transfer Learning. SDM 2015: 514-522 - [c41]Pei Yang, Jingrui He, Jia-Yu Pan:
Learning Complex Rare Categories with Dual Heterogeneity. SDM 2015: 523-531 - 2014
- [c40]Pei Yang, Jingrui He, Hongxia Yang, Haoda Fu:
Learning from Label and Feature Heterogeneity. ICDM 2014: 1079-1084 - [c39]Yada Zhu, Jingrui He:
Co-Clustering Structural Temporal Data with Applications to Semiconductor Manufacturing. ICDM 2014: 1121-1126 - [c38]Hongxia Yang, Jingrui He:
Learning with dual heterogeneity: a nonparametric bayes model. KDD 2014: 582-590 - [c37]Jingrui He, Yan Liu, Qiang Yang:
Linking Heterogeneous Input Spaces with Pivots for Multi-Task Learning. SDM 2014: 181-189 - [r1]Jingrui He, Yada Zhu:
Social Engineering/Phishing. Encyclopedia of Social Network Analysis and Mining 2014: 1777-1783 - 2013
- [c36]Dan Zhang, Jingrui He, Luo Si, Richard D. Lawrence:
MILEAGE: Multiple Instance LEArning with Global Embedding. ICML (3) 2013: 82-90 - [c35]Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence:
Improving Traffic Prediction with Tweet Semantics. IJCAI 2013: 1387-1393 - [c34]Dan Zhang, Jingrui He, Richard D. Lawrence:
MI2LS: multi-instance learning from multiple informationsources. KDD 2013: 149-157 - [e1]Inderjit S. Dhillon, Yehuda Koren, Rayid Ghani, Ted E. Senator, Paul Bradley, Rajesh Parekh, Jingrui He, Robert L. Grossman, Ramasamy Uthurusamy:
The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013. ACM 2013, ISBN 978-1-4503-2174-7 [contents] - 2012
- [b1]Jingrui He:
Analysis of Rare Categories. Cognitive Technologies, Springer 2012, ISBN 978-3-642-22812-4, pp. 1-128 - [j5]Jingrui He, Hanghang Tong, Jaime G. Carbonell:
An effective framework for characterizing rare categories. Frontiers Comput. Sci. 6(2): 154-165 (2012) - [c33]Yada Zhu, Jingrui He, Rick Lawrence:
Hierarchical Modeling with Tensor Inputs. AAAI 2012: 1233-1239 - [c32]Jingrui He, Yada Zhu:
Hierarchical Multi-task Learning with Application to Wafer Quality Prediction. ICDM 2012: 290-298 - [c31]Jingrui He, Hanghang Tong, Qiaozhu Mei, Boleslaw K. Szymanski:
GenDeR: A Generic Diversified Ranking Algorithm. NIPS 2012: 1151-1159 - [c30]Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbonell:
Adaptive Multi-task Sparse Learning with an Application to fMRI Study. SDM 2012: 212-223 - 2011
- [c29]Jingrui He, Rick Lawrence:
A Graphbased Framework for Multi-Task Multi-View Learning. ICML 2011: 25-32 - [c28]Hanghang Tong, Jingrui He, Zhen Wen, Ravi B. Konuru, Ching-Yung Lin:
Diversified ranking on large graphs: an optimization viewpoint. KDD 2011: 1028-1036 - [c27]Dan Zhang, Jingrui He, Yan Liu, Luo Si, Richard D. Lawrence:
Multi-view transfer learning with a large margin approach. KDD 2011: 1208-1216 - 2010
- [j4]Jingrui He, Jaime G. Carbonell:
Coselection of features and instances for unsupervised rare category analysis. Stat. Anal. Data Min. 3(6): 417-430 (2010) - [c26]Jingrui He, Hanghang Tong, Jaime G. Carbonell:
Rare Category Characterization. ICDM 2010: 226-235 - [c25]Jingrui He, Qing He, Grzegorz Swirszcz, Yiannis Kamarianakis, Rick Lawrence, Wei Shen, Laura Wynter:
Ensemble-Based Method for Task 2: Predicting Traffic Jam. ICDM Workshops 2010: 1363-1365 - [c24]Wei Shen, Yiannis Kamarianakis, Laura Wynter, Jingrui He, Qing He, Rick Lawrence, Grzegorz Swirszcz:
Traffic Velocity Prediction Using GPS Data: IEEE ICDM Contest Task 3 Report. ICDM Workshops 2010: 1369-1371 - [c23]Jingrui He, Jaime G. Carbonell:
Co-selection of Features and Instances for Unsupervised Rare Category Analysis. SDM 2010: 525-536
2000 – 2009
- 2009
- [c22]Jingrui He, Yan Liu, Richard D. Lawrence:
Graph-based transfer learning. CIKM 2009: 937-946 - [c21]Jingrui He, Jaime G. Carbonell:
Prior-Free Rare Category Detection. SDM 2009: 155-163 - 2008
- [c20]Jingrui He, Yan Liu, Richard D. Lawrence:
Graph-Based Rare Category Detection. ICDM 2008: 833-838 - [c19]Jingrui He, Jaime G. Carbonell:
Rare Class Discovery Based on Active Learning. ISAIM 2008 - 2007
- [j3]Fei Wu, Changshui Zhang, Jingrui He:
An evolutionary system for near-regular texture synthesis. Pattern Recognit. 40(8): 2271-2282 (2007) - [c18]Jingrui He, Bo Thiesson:
Asymmetric Gradient Boosting with Application to Spam Filtering. CEAS 2007 - [c17]Jingrui He, Jaime G. Carbonell, Yan Liu:
Graph-Based Semi-Supervised Learning as a Generative Model. IJCAI 2007: 2492-2497 - [c16]Jingrui He, Jaime G. Carbonell:
Nearest-Neighbor-Based Active Learning for Rare Category Detection. NIPS 2007: 633-640 - 2006
- [j2]Hanghang Tong, Jingrui He, Mingjing Li, Wei-Ying Ma, Hong-Jiang Zhang, Changshui Zhang:
Manifold-Ranking-Based Keyword Propagation for Image Retrieval. EURASIP J. Adv. Signal Process. 2006 (2006) - [j1]Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang Tong, Changshui Zhang:
Generalized Manifold-Ranking-Based Image Retrieval. IEEE Trans. Image Process. 15(10): 3170-3177 (2006) - 2005
- [c15]Hanghang Tong, Jingrui He, Mingjing Li, Wei-Ying Ma, Changshui Zhang, HongJiang Zhang:
A Unified Optimization Based Learning Method for Image Retrieval. CVPR (2) 2005: 230-235 - [c14]Jingrui He, Changshui Zhang, Nanyuan Zhao, Hanghang Tong:
Boosting Web Image Search by Co-Ranking. ICASSP (2) 2005: 409-412 - [c13]Hanghang Tong, Chongrong Li, Jingrui He, Yang Chen:
Internet Traffic Prediction by W-Boost: Classification and Regression. ISNN (3) 2005: 397-402 - [c12]Hanghang Tong, Chongrong Li, Jingrui He, Jiajian Chen, Quang-Anh Tran, Hai-Xin Duan, Xing Li:
Anomaly Internet Network Traffic Detection by Kernel Principle Component Classifier. ISNN (3) 2005: 476-481 - [c11]Jingrui He, Hanghang Tong, Mingjing Li, Wei-Ying Ma, Changshui Zhang:
Multiple random walk and its application in content-based image retrieval. Multimedia Information Retrieval 2005: 151-158 - [c10]Hanghang Tong, Jingrui He, Mingjing Li, Changshui Zhang, Wei-Ying Ma:
Graph based multi-modality learning. ACM Multimedia 2005: 862-871 - [c9]Hanghang Tong, Mingjing Li, HongJiang Zhang, Changshui Zhang, Jingrui He, Wei-Ying Ma:
Learning No-Reference Quality Metric by Examples. MMM 2005: 247-254 - 2004
- [c8]Jingrui He, Mingjing Li, HongJiang Zhang, Changshui Zhang:
Symmetry feature in content-based image retrieval. ICIP 2004: 417-420 - [c7]Jingrui He, Mingjing Li, HongJiang Zhang, Changshui Zhang:
W-Boost and Its Application to Web Image Classification. ICPR (1) 2004: 148-151 - [c6]Hanghang Tong, Chongrong Li, Jingrui He:
A Boosting-Based Framework for Self-Similar and Non-linear Internet Traffic Prediction. ISNN (2) 2004: 931-936 - [c5]Jingrui He, Hanghang Tong, Mingjing Li, HongJiang Zhang, Changshui Zhang:
Mean version space: a new active learning method for content-based image retrieval. Multimedia Information Retrieval 2004: 15-22 - [c4]Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang Tong, Changshui Zhang:
Manifold-ranking based image retrieval. ACM Multimedia 2004: 9-16 - [c3]Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang Tong, Changshui Zhang:
Automatic Peak Number Detection in Image Symmetry Analysis. PCM (3) 2004: 111-118 - [c2]Hanghang Tong, Mingjing Li, HongJiang Zhang, Jingrui He, Changshui Zhang:
Classification of Digital Photos Taken by Photographers or Home Users. PCM (1) 2004: 198-205 - [c1]Jingrui He, Mingjing Li, Zhiwei Li, HongJiang Zhang, Hanghang Tong, Changshui Zhang:
Pseudo Relevance Feedback Based on Iterative Probabilistic One-Class SVMs in Web Image Retrieval. PCM (2) 2004: 213-220
Coauthor Index
[j32] [c149] [c148] [c144] [c143] [c141] [c140] [i59] [i58] [i57] [i55] [i51] [j30] [c121] [i49] [i46] [i43] [j25] [c118] [c114] [c103] [c102] [i34] [i30] [i26] [j23] [i15] [c91] [c90] [c89] [j18] [c80] [c78] [i6] [c66] [j10] [c61] [c58] [c57] [c49] [j5] [c31] [c28] [c26] [j2] [j1] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c6] [c5] [c4] [c3] [c2] [c1]
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