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ORCIDXingquan Zhu 0001
Hill Zhu
Person information
- affiliation: Florida Atlantic University, Department of Computer & Electrical Engineering and Computer Science, Boca Raton, FL, USA
- affiliation (former): University of Technology Sydney, Faculty of Engineering and Information Technology, NSW, Australia
- affiliation (PhD): Fudan University, Shanghai, China
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2020 – today
- 2023
[j129]Divya Gangwani, Xingquan Zhu, Borko Furht:
Exploring investor-business-market interplay for business success prediction. J. Big Data 10(1): 48 (2023)- [j128]Youxi Wu
, Qian Hu, Yan Li, Lei Guo, Xingquan Zhu, Xindong Wu:
OPP-Miner: Order-Preserving Sequential Pattern Mining for Time Series. IEEE Trans. Cybern. 53(5): 3288-3300 (2023) - [j127]Yaojin Lin, Haoyang Liu, Hong Zhao, Qinghua Hu, Xingquan Zhu, Xindong Wu:
Hierarchical Feature Selection Based on Label Distribution Learning. IEEE Trans. Knowl. Data Eng. 35(6): 5964-5976 (2023) - [c176]Boyu Li, Ting Guo, Xingquan Zhu, Qian Li, Yang Wang, Fang Chen:
SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation. WSDM 2023: 589-597 - 2022
- [j126]Yu Huang, Yufei Tang, Xingquan Zhu, Hanqi Zhuang, Laurent M. Chérubin:
Physics-Coupled Spatio-Temporal Active Learning for Dynamical Systems. IEEE Access 10: 112909-112920 (2022) - [j125]Guoqing Chao, Xingquan Zhu, Weiping Ding, Jinbo Bi, Shiliang Sun:
Editorial: special issue on multi-view learning. Appl. Intell. 52(13): 14591-14594 (2022) - [j124]Zhabiz Gharibshah, Xingquan Zhu:
User Response Prediction in Online Advertising. ACM Comput. Surv. 54(3): 64:1-64:43 (2022) - [j123]Qiang Zhu, Xingquan Zhu, Yicheng Tu:
Introduction to special issue on scientific and statistical data management in the age of AI 2021. Distributed Parallel Databases 40(2-3): 201-204 (2022) - [j122]Shuwen Wang, Xingquan Zhu:
Nationwide hospital admission data statistics and disease-specific 30-day readmission prediction. Health Inf. Sci. Syst. 10(1): 25 (2022) - [j121]Shuwen Wang, Xingquan Zhu, Weiping Ding, Amir Alipour Yengejeh:
Cyberbullying and Cyberviolence Detection: A Triangular User-Activity-Content View. IEEE CAA J. Autom. Sinica 9(8): 1384-1405 (2022) - [j120]Min Shi, Yufei Tang, Xingquan Zhu, Yu Huang, David A. Wilson, Yuan Zhuang, Jianxun Liu:
Genetic-GNN: Evolutionary architecture search for Graph Neural Networks. Knowl. Based Syst. 247: 108752 (2022) - [j119]Min Shi, Yufei Tang, Xingquan Zhu, Jianxun Liu:
Multi-Label Graph Convolutional Network Representation Learning. IEEE Trans. Big Data 8(5): 1169-1181 (2022) - [j118]Shuwen Wang, Xingquan Zhu:
Predictive Modeling of Hospital Readmission: Challenges and Solutions. IEEE ACM Trans. Comput. Biol. Bioinform. 19(5): 2975-2995 (2022) - [j117]Min Shi, Yufei Tang, Xingquan Zhu, Yuan Zhuang, Maohua Lin, Jianxun Liu:
Feature-Attention Graph Convolutional Networks for Noise Resilient Learning. IEEE Trans. Cybern. 52(8): 7719-7731 (2022) - [j116]Youxi Wu, Yuehua Wang, Yan Li, Xingquan Zhu, Xindong Wu:
Top-k Self-Adaptive Contrast Sequential Pattern Mining. IEEE Trans. Cybern. 52(11): 11819-11833 (2022) - [j115]Man Wu, Shirui Pan, Xingquan Zhu:
Attraction and Repulsion: Unsupervised Domain Adaptive Graph Contrastive Learning Network. IEEE Trans. Emerg. Top. Comput. Intell. 6(5): 1079-1091 (2022) - [j114]Yaojin Lin, Qinghua Hu, Jinghua Liu, Xingquan Zhu, Xindong Wu:
MULFE: Multi-Label Learning via Label-Specific Feature Space Ensemble. ACM Trans. Knowl. Discov. Data 16(1): 5:1-5:24 (2022) - [j113]Youxi Wu, Lanfang Luo, Yan Li, Lei Guo, Philippe Fournier-Viger, Xingquan Zhu, Xindong Wu:
NTP-Miner: Nonoverlapping Three-Way Sequential Pattern Mining. ACM Trans. Knowl. Discov. Data 16(3): 51:1-51:21 (2022) - [j112]Pengfei Ma, Youxi Wu, Yan Li, Lei Guo, He Jiang, Xingquan Zhu, Xindong Wu:
HW-Forest: Deep Forest with Hashing Screening and Window Screening. ACM Trans. Knowl. Discov. Data 16(6): 123:1-123:24 (2022) - [j111]Xiaofei Zhou, Lingfeng Niu, Qiannan Zhu, Xingquan Zhu, Ping Liu, Jianlong Tan, Li Guo:
Knowledge Graph Embedding by Double Limit Scoring Loss. IEEE Trans. Knowl. Data Eng. 34(12): 5825-5839 (2022) - [j110]Xindong Wu, Xingquan Zhu, Minghui Wu:
The Evolution of Search: Three Computing Paradigms. ACM Trans. Manag. Inf. Syst. 13(2): 20:1-20:20 (2022) - [j109]Min Shi, Yufei Tang, Xingquan Zhu:
Topology and Content Co-Alignment Graph Convolutional Learning. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7899-7907 (2022) - [j108]Min Shi, Yuan Zhuang, Yufei Tang, Maohua Lin, Xingquan Zhu, Jianxun Liu:
Web Service Network Embedding Based on Link Prediction and Convolutional Learning. IEEE Trans. Serv. Comput. 15(6): 3620-3633 (2022) - [c175]Man Wu, Xingquan Zhu:
Temporal Adaptive Aggregation Network for Dynamic Graph Learning. Big Data 2022: 806-811 - [c174]Yufei Jin, Xingquan Zhu:
Predictive Masking for Semi-Supervised Graph Contrastive Learning. Big Data 2022: 1266-1271 - [c173]Zhabiz Gharibshah, Xingquan Zhu:
Local Contrastive Feature Learning for Tabular Data. CIKM 2022: 3963-3967 - [c172]Cihan Ulus, Zhiqiang Wang, Sheikh M. A. Iqbal, K. Md. Salman Khan, Xingquan Zhu:
Transfer Naïve Bayes Learning using Augmentation and Stacking for SMS Spam Detection. ICKG 2022: 275-282 - [c171]Xingquan Zhu, Sanjay Ranka:
Message from the ICDM 2022 Program Committee Chairs. ICDM (Workshops) 2022: xxvii-xxviii - [e5]Xingquan Zhu, Sanjay Ranka, My T. Thai, Takashi Washio, Xindong Wu:
IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA, November 28 - Dec. 1, 2022. IEEE 2022, ISBN 978-1-6654-5099-7 [contents] - [i23]Youxi Wu, Qian Hu, Yan Li, Lei Guo, Xingquan Zhu, Xindong Wu:
OPP-Miner: Order-preserving sequential pattern mining. CoRR abs/2202.03140 (2022) - [i22]Pengfei Ma, Youxi Wu, Yan Li, Lei Guo, He Jiang, Xingquan Zhu, Xindong Wu:
Deep Forest with Hashing Screening and Window Screening. CoRR abs/2207.11951 (2022) - [i21]Youxi Wu, Xiaoqian Zhao, Yan Li, Lei Guo, Xingquan Zhu, Philippe Fournier-Viger, Xindong Wu:
OPR-Miner: Order-preserving rule mining for time series. CoRR abs/2209.08932 (2022) - [i20]Zhabiz Gharibshah, Xingquan Zhu:
Local Contrastive Feature learning for Tabular Data. CoRR abs/2211.10549 (2022) - 2021
- [j107]Shuliang Wang, Qi Li, Chuanfeng Zhao, Xingquan Zhu, Hanning Yuan, Tianru Dai:
Extreme clustering - A clustering method via density extreme points. Inf. Sci. 542: 24-39 (2021) - [j106]Man Wu, Shirui Pan, Xingquan Zhu:
OpenWGL: open-world graph learning for unseen class node classification. Knowl. Inf. Syst. 63(9): 2405-2430 (2021) - [j105]Youxi Wu, Meng Geng, Yan Li, Lei Guo, Zhao Li, Philippe Fournier-Viger, Xingquan Zhu, Xindong Wu:
HANP-Miner: High average utility nonoverlapping sequential pattern mining. Knowl. Based Syst. 229: 107361 (2021) - [j104]Magdalyn E. Elkin, Xingquan Zhu:
Community and topic modeling for infectious disease clinical trial recommendation. Netw. Model. Anal. Health Informatics Bioinform. 10(1): 47 (2021) - [j103]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Search Efficient Binary Network Embedding. ACM Trans. Knowl. Discov. Data 15(4): 61:1-61:27 (2021) - [j102]Man Wu, Shirui Pan, Lan Du, Xingquan Zhu:
Learning Graph Neural Networks with Positive and Unlabeled Nodes. ACM Trans. Knowl. Discov. Data 15(6): 101:1-101:25 (2021) - [c170]Yu Huang, Chao Zhang, Jaswanth K. Yella, Sergei Petrov, Xiaoye Qian, Yufei Tang, Xingquan Zhu, Sthitie Bom:
GraSSNet: Graph Soft Sensing Neural Networks. IEEE BigData 2021: 746-756 - [c169]Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen:
Graph Compression Networks. IEEE BigData 2021: 1030-1036 - [c168]Jose Delgado, Xingquan Zhu, Karin Scarpinato, Jason O. Hallstrom, Terje Hill:
Understanding and Predicting Faculty Success in Winning Grant Awards. IEEE BigData 2021: 5881 - [c167]Divya Gangwani, Qianxin Liang, Shuwen Wang, Xingquan Zhu:
An Empirical Study of Deep Learning Frameworks for Melanoma Cancer Detection using Transfer Learning and Data Augmentation. ICBK 2021: 38-45 - [c166]Min Shi, Yu Huang, Xingquan Zhu, Yufei Tang, Yuan Zhuang, Jianxun Liu:
GAEN: Graph Attention Evolving Networks. IJCAI 2021: 1541-1547 - [c165]Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen:
Weak Supervision Network Embedding for Constrained Graph Learning. PAKDD (1) 2021: 488-500 - [e4]Yixin Chen, Heiko Ludwig, Yicheng Tu, Usama M. Fayyad, Xingquan Zhu, Xiaohua Hu, Suren Byna, Xiong Liu, Jianping Zhang, Shirui Pan, Vagelis Papalexakis, Jianwu Wang, Alfredo Cuzzocrea, Carlos Ordonez:
2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, December 15-18, 2021. IEEE 2021, ISBN 978-1-6654-3902-2 [contents] - [e3]Qiang Zhu, Xingquan Zhu, Yicheng Tu, Zichen Xu, Anand Kumar:
SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, Tampa, FL, USA, July 6-7, 2021. ACM 2021, ISBN 978-1-4503-8413-1 [contents] - [i19]Zhabiz Gharibshah, Xingquan Zhu:
User Response Prediction in Online Advertising. CoRR abs/2101.02342 (2021) - [i18]Man Wu, Shirui Pan, Lan Du, Xingquan Zhu:
Learning Graph Neural Networks with Positive and Unlabeled Nodes. CoRR abs/2103.04683 (2021) - [i17]Shuwen Wang, Xingquan Zhu:
Predictive Modeling of Hospital Readmission: Challenges and Solutions. CoRR abs/2106.08488 (2021) - [i16]Yu Huang, Yufei Tang, Xingquan Zhu, Min Shi, Ali Muhamed Ali, Hanqi Zhuang, Laurent M. Chérubin:
Physics-Coupled Spatio-Temporal Active Learning for Dynamical Systems. CoRR abs/2108.05385 (2021) - [i15]Yu Huang, James Li, Min Shi, Hanqi Zhuang, Xingquan Zhu, Laurent M. Chérubin, James H. VanZwieten, Yufei Tang:
ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting. CoRR abs/2108.05940 (2021) - [i14]Yu Huang, Chao Zhang, Jaswanth K. Yella, Sergei Petrov, Xiaoye Qian, Yufei Tang, Xingquan Zhu, Sthitie Bom:
GraSSNet: Graph Soft Sensing Neural Networks. CoRR abs/2111.06980 (2021) - 2020
- [j101]Zhabiz Gharibshah, Xingquan Zhu, Arthur Hainline, Michael Conway:
Deep Learning for User Interest and Response Prediction in Online Display Advertising. Data Sci. Eng. 5(1): 12-26 (2020) - [j100]Min Shi, Yufei Tang, Xingquan Zhu, Jianxun Liu, Haibo He:
Topical network embedding. Data Min. Knowl. Discov. 34(1): 75-100 (2020) - [j99]Christian Garbin, Xingquan Zhu, Oge Marques:
Dropout vs. batch normalization: an empirical study of their impact to deep learning. Multim. Tools Appl. 79(19-20): 12777-12815 (2020) - [j98]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Network Representation Learning: A Survey. IEEE Trans. Big Data 6(1): 3-28 (2020) - [j97]Huimei Han, Xingquan Zhu, Ying Li:
Generalizing Long Short-Term Memory Network for Deep Learning from Generic Data. ACM Trans. Knowl. Discov. Data 14(2): 13:1-13:28 (2020) - [j96]Min Shi, Yufei Tang, Xingquan Zhu:
MLNE: Multi-Label Network Embedding. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3682-3695 (2020) - [j95]Haishuai Wang, Jia Wu, Xingquan Zhu, Yixin Chen, Chengqi Zhang:
Time-Variant Graph Classification. IEEE Trans. Syst. Man Cybern. Syst. 50(8): 2883-2896 (2020) - [j94]Min Shi, Yufei Tang, Xingquan Zhu, Jianxun Liu:
Topic-aware Web Service Representation Learning. ACM Trans. Web 14(2): 9:1-9:23 (2020) - [j93]Jorge Agnese, Jonathan Herrera, Haicheng Tao, Xingquan Zhu:
A survey and taxonomy of adversarial neural networks for text-to-image synthesis. WIREs Data Mining Knowl. Discov. 10(4) (2020) - [c164]Anak Wannaphaschaiyong, Xingquan Zhu:
COPD Disease Classification Using Network Embedding with Synthetic Relationships. FLAIRS 2020: 217-221 - [c163]Yuping Su, Xingquan Zhu, Bei Dong, Yumei Zhang, Xiaojun Wu:
MedFroDetect: Medicare Fraud Detection with Extremely Imbalanced Class Distributions. FLAIRS 2020: 357-361 - [c162]Shuwen Wang, Magdalyn E. Elkin, Xingquan Zhu:
Imbalanced Learning for Hospital Readmission Prediction using National Readmission Database. ICKG 2020: 116-122 - [c161]Lukasz Chmielewski, Rafina Amin, Anak Wannaphaschaiyong, Xingquan Zhu:
Network Analysis of Technology Stocks using Market Correlation. ICKG 2020: 267-274 - [c160]Zhabiz Gharibshah, Xingquan Zhu:
TriNE: Network Representation Learning for Tripartite Heterogeneous Networks. ICKG 2020: 497-504 - [c159]Man Wu, Shirui Pan, Xingquan Zhu:
OpenWGL: Open-World Graph Learning. ICDM 2020: 681-690 - [c158]Min Shi, Yufei Tang, Xingquan Zhu, David A. Wilson, Jianxun Liu:
Multi-Class Imbalanced Graph Convolutional Network Learning. IJCAI 2020: 2879-2885 - [c157]Man Wu, Shirui Pan, Chuan Zhou, Xiaojun Chang, Xingquan Zhu:
Unsupervised Domain Adaptive Graph Convolutional Networks. WWW 2020: 1457-1467 - [i13]Min Shi, Yufei Tang, Xingquan Zhu:
Topology and Content Co-Alignment Graph Convolutional Learning. CoRR abs/2003.12806 (2020) - [i12]Min Shi, David A. Wilson, Xingquan Zhu, Yu Huang, Yuan Zhuang, Jianxun Liu, Yufei Tang:
Evolutionary Architecture Search for Graph Neural Networks. CoRR abs/2009.10199 (2020) - [i11]Zhabiz Gharibshah, Xingquan Zhu:
TriNE: Network Representation Learning for Tripartite Heterogeneous Networks. CoRR abs/2010.06816 (2020)
2010 – 2019
- 2019
- [j92]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Attributed network embedding via subspace discovery. Data Min. Knowl. Discov. 33(6): 1953-1980 (2019) - [j91]Huimei Han, Ying Li, Xingquan Zhu:
Convolutional neural network learning for generic data classification. Inf. Sci. 477: 448-465 (2019) - [j90]Eric Golinko, Xingquan Zhu:
Generalized Feature Embedding for Supervised, Unsupervised, and Online Learning Tasks. Inf. Syst. Frontiers 21(1): 125-142 (2019) - [j89]Bozhong Liu, Ling Chen, Xingquan Zhu, Weidong Qiu:
Encrypted data indexing for the secure outsourcing of spectral clustering. Knowl. Inf. Syst. 60(3): 1307-1328 (2019) - [j88]Ting Guo, Shirui Pan, Xingquan Zhu, Chengqi Zhang:
CFOND: Consensus Factorization for Co-Clustering Networked Data. IEEE Trans. Knowl. Data Eng. 31(4): 706-719 (2019) - [c156]Zhabiz Gharibshah, Xingquan Zhu, Arthur Hainline, Michael Conway:
Deep Learning for Online Display Advertising User Clicks and Interests Prediction. APWeb/WAIM (1) 2019: 196-204 - [c155]Magdalyn E. Elkin, Whitney Angelica Andrews, Xingquan Zhu:
Network Analysis and Recommendation for Infectious Disease Clinical Trial Research. BCB 2019: 347-356 - [c154]Man Wu, Shirui Pan, Lan Du, Ivor W. Tsang, Xingquan Zhu, Bo Du:
Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning. CIKM 2019: 2157-2160 - [c153]Man Wu, Shirui Pan, Xingquan Zhu, Chuan Zhou, Lei Pan:
Domain-Adversarial Graph Neural Networks for Text Classification. ICDM 2019: 648-657 - [c152]Shichao Zhu, Chuan Zhou, Shirui Pan, Xingquan Zhu, Bin Wang:
Relation Structure-Aware Heterogeneous Graph Neural Network. ICDM 2019: 1534-1539 - [c151]Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen:
Discriminative Sample Generation for Deep Imbalanced Learning. IJCAI 2019: 2406-2412 - [i10]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Attributed Network Embedding via Subspace Discovery. CoRR abs/1901.04095 (2019) - [i9]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Search Efficient Binary Network Embedding. CoRR abs/1901.04097 (2019) - [i8]Jorge Agnese, Jonathan Herrera, Haicheng Tao, Xingquan Zhu:
A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis. CoRR abs/1910.09399 (2019) - [i7]Min Shi, Yufei Tang, Xingquan Zhu, Jianxun Liu:
Feature-Attention Graph Convolutional Networks for Noise Resilient Learning. CoRR abs/1912.11755 (2019) - [i6]Min Shi, Yufei Tang, Xingquan Zhu, Jianxun Liu:
Multi-Label Graph Convolutional Network Representation Learning. CoRR abs/1912.11757 (2019) - 2018
- [j87]Lianhua Chi, Bin Li, Xingquan Zhu, Shirui Pan, Ling Chen:
Hashing for Adaptive Real-Time Graph Stream Classification With Concept Drifts. IEEE Trans. Cybern. 48(5): 1591-1604 (2018) - [j86]Youxi Wu, Yao Tong, Xingquan Zhu, Xindong Wu:
NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints. IEEE Trans. Cybern. 48(10): 2809-2822 (2018) - [j85]Ankur Agarwal, Christopher Baechle, Ravi S. Behara, Xingquan Zhu:
A Natural Language Processing Framework for Assessing Hospital Readmissions for Patients With COPD. IEEE J. Biomed. Health Informatics 22(2): 588-596 (2018) - [j84]Wei Wu, Bin Li, Ling Chen, Xingquan Zhu, Chengqi Zhang:
K-Ary Tree Hashing for Fast Graph Classification. IEEE Trans. Knowl. Data Eng. 30(5): 936-949 (2018) - [j83]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Xindong Wu:
Multi-Instance Learning with Discriminative Bag Mapping. IEEE Trans. Knowl. Data Eng. 30(6): 1065-1080 (2018) - [j82]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Multiple Structure-View Learning for Graph Classification. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3236-3251 (2018) - [j81]Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu:
A Novel Consistent Random Forest Framework: Bernoulli Random Forests. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3510-3523 (2018) - [c150]Huimei Han, Xingquan Zhu, Ying Li:
EDLT: Enabling Deep Learning for Generic Data Classification. ICDM 2018: 147-156 - [c149]Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, Jilong Wang:
Deep Structure Learning for Fraud Detection. ICDM 2018: 567-576 - [c148]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
SINE: Scalable Incomplete Network Embedding. ICDM 2018: 737-746 - [c147]Eric Golinko, Thomas Sonderman, Xingquan Zhu:
Learning Convolutional Neural Networks from Ordered Features of Generic Data. ICMLA 2018: 897-900 - [c146]Grant Rosario, Thomas Sonderman, Xingquan Zhu:
Deep Transfer Learning for Traffic Sign Recognition. IRI 2018: 178-185 - [c145]Charles Wheelus, Elias Bou-Harb, Xingquan Zhu:
Tackling Class Imbalance in Cyber Security Datasets. IRI 2018: 229-232 - [c144]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding. PAKDD (2) 2018: 196-208 - [r2]Xingquan Zhu:
Quantitative Association Rules. Encyclopedia of Database Systems (2nd ed.) 2018 - [i5]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Network Representation Learning: A Survey. CoRR abs/1801.05852 (2018) - [i4]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding. CoRR abs/1803.02533 (2018) - [i3]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
SINE: Scalable Incomplete Network Embedding. CoRR abs/1810.06768 (2018) - 2017
- [b1]Xingquan Zhu, Haicheng Tao, Zhiang Wu, Jie Cao, Kristopher Kalish, Jeremy Kayne:
Fraud Prevention in Online Digital Advertising. Springer Briefs in Computer Science, Springer 2017, ISBN 978-3-319-56792-1, pp. 1-51 - [j80]Lianhua Chi, Xingquan Zhu:
Hashing Techniques: A Survey and Taxonomy. ACM Comput. Surv. 50(1): 11:1-11:36 (2017) - [j79]Christopher Baechle, Ankur Agarwal, Xingquan Zhu:
Big data driven co-occurring evidence discovery in chronic obstructive pulmonary disease patients. J. Big Data 4: 9 (2017) - [j78]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Boosting for graph classification with universum. Knowl. Inf. Syst. 50(1): 53-77 (2017) - [j77]Fei Xie, Xindong Wu, Xingquan Zhu:
Efficient sequential pattern mining with wildcards for keyphrase extraction. Knowl. Based Syst. 115: 27-39 (2017) - [j76]Dongkuan Xu, Jia Wu, Dewei Li, Yingjie Tian, Xingquan Zhu, Xindong Wu:
SALE: Self-adaptive LSH encoding for multi-instance learning. Pattern Recognit. 71: 460-482 (2017) - [j75]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Task Sensitive Feature Exploration and Learning for Multitask Graph Classification. IEEE Trans. Cybern. 47(3): 744-758 (2017) - [j74]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Xindong Wu:
Positive and Unlabeled Multi-Graph Learning. IEEE Trans. Cybern. 47(4): 818-829 (2017) - [j73]Ting Guo, Jia Wu, Xingquan Zhu, Chengqi Zhang:
Combining Structured Node Content and Topology Information for Networked Graph Clustering. ACM Trans. Knowl. Discov. Data 11(3): 29:1-29:29 (2017) - [j72]Haishuai Wang, Peng Zhang, Xingquan Zhu, Ivor Wai-Hung Tsang, Ling Chen, Chengqi Zhang, Xindong Wu:
Incremental Subgraph Feature Selection for Graph Classification. IEEE Trans. Knowl. Data Eng. 29(1): 128-142 (2017) - [c143]Christopher Baechle, Ankur Agarwal, Ravi S. Behara, Xingquan Zhu:
A cost sensitive approach to predicting 30-day hospital readmission in COPD patients. BHI 2017: 317-320 - [c142]Christopher Baechle, Ankur Agarwal, Ravi S. Behara, Xingquan Zhu:
Co-occurring evidence discovery for COPD patients using natural language processing. BHI 2017: