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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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Books and Theses
- 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
Journal Articles
- 2024
- [j138]Matteo Zaramella
, Xingquan Zhu, Irene Amerini:
Enhancing Manatee Aggregation Counting Through Augmentation and Cross-Domain Learning. IEEE Access 12: 131148-131163 (2024) - [j137]Divya Gangwani, Xingquan Zhu:
Modeling and prediction of business success: a survey. Artif. Intell. Rev. 57(2): 44 (2024) - [j136]Mostapha Alsaidi, Muhammad Tanveer Jan, Ahmed Altaher, Hanqi Zhuang, Xingquan Zhu:
Tackling the class imbalanced dermoscopic image classification using data augmentation and GAN. Multim. Tools Appl. 83(16): 49121-49147 (2024) - [j135]Haicheng Tao, Jie Cao, Lei Chen, Hong-Liang Sun, Yong Shi, Xingquan Zhu:
Black-box attacks on dynamic graphs via adversarial topology perturbations. Neural Networks 171: 308-319 (2024) - [j134]Youxi Wu, Yufei Meng, Yan Li, Lei Guo, Xingquan Zhu, Philippe Fournier-Viger, Xindong Wu:
COPP-Miner: Top-k Contrast Order-Preserving Pattern Mining for Time Series Classification. IEEE Trans. Knowl. Data Eng. 36(6): 2372-2387 (2024) - [j133]Meng Geng, Youxi Wu, Yan Li, Jing Liu, Philippe Fournier-Viger, Xingquan Zhu, Xindong Wu:
RNP-Miner: Repetitive Nonoverlapping Sequential Pattern Mining. IEEE Trans. Knowl. Data Eng. 36(9): 4874-4889 (2024) - [j132]Youxi Wu, Zhen Wang, Yan Li, Yingchun Guo, He Jiang, Xingquan Zhu, Xindong Wu:
Co-occurrence Order-preserving Pattern Mining with Keypoint Alignment for Time Series. ACM Trans. Manag. Inf. Syst. 15(2): 9 (2024) - 2023
- [j131]Divya Gangwani, Xingquan Zhu, Borko Furht:
Exploring investor-business-market interplay for business success prediction. J. Big Data 10(1): 48 (2023) - [j130]Guoqing Chao, Xingquan Zhu, Weiping Ding, Jinbo Bi, Shiliang Sun:
Editorial: Special Issue on Transfer Learning. Neural Process. Lett. 55(3): 1997-2000 (2023) - [j129]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) - [j128]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) - [j127]Youxi Wu, Xiaoqian Zhao, Yan Li, Lei Guo, Xingquan Zhu, Philippe Fournier-Viger, Xindong Wu:
OPR-Miner: Order-Preserving Rule Mining for Time Series. IEEE Trans. Knowl. Data Eng. 35(11): 11722-11735 (2023) - 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) - 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) - 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) - 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) - 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) - 2017
- [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) - 2016
- [j71]Meng Fang, Jie Yin, Xingquan Zhu:
Active exploration for large graphs. Data Min. Knowl. Discov. 30(3): 511-549 (2016) - [j70]Jose Hurtado, Ankur Agarwal, Xingquan Zhu:
Topic discovery and future trend forecasting for texts. J. Big Data 3: 7 (2016) - [j69]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-graph-view subgraph mining for graph classification. Knowl. Inf. Syst. 48(1): 29-54 (2016) - [j68]Jia Wu, Shirui Pan, Xingquan Zhu, Peng Zhang, Chengqi Zhang:
SODE: Self-Adaptive One-Dependence Estimators for classification. Pattern Recognit. 51: 358-377 (2016) - [j67]Meng Fang, Jie Yin, Xingquan Zhu:
Supervised sampling for networked data. Signal Process. 124: 93-102 (2016) - [j66]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Joint Structure Feature Exploration and Regularization for Multi-Task Graph Classification. IEEE Trans. Knowl. Data Eng. 28(3): 715-728 (2016) - 2015
- [j65]Boyu Li, Ting Guo, Xingquan Zhu, Zhanshan Li:
Reverse twin plant for efficient diagnosability testing and optimizing. Eng. Appl. Artif. Intell. 38: 131-137 (2015) - [j64]Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai, Peng Zhang, Chengqi Zhang:
Self-adaptive attribute weighting for Naive Bayes classification. Expert Syst. Appl. 42(3): 1487-1502 (2015) - [j63]Anand Kumar, Vladimir Grupcev, Meryem Berrada, Joseph C. Fogarty, Yi-Cheng Tu, Xingquan Zhu, Sagar A. Pandit, Yuni Xia:
DCMS: A data analytics and management system for molecular simulation. J. Big Data 2: 9 (2015) - [j62]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Finding the best not the most: regularized loss minimization subgraph selection for graph classification. Pattern Recognit. 48(11): 3783-3796 (2015) - [j61]Buyun Qu, Zhibin Zhang, Xingquan Zhu, Dan Meng:
An empirical study of morphing on behavior-based network traffic classification. Secur. Commun. Networks 8(1): 68-79 (2015) - [j60]Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai:
Boosting for Multi-Graph Classification. IEEE Trans. Cybern. 45(3): 430-443 (2015) - [j59]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang:
Graph Ensemble Boosting for Imbalanced Noisy Graph Stream Classification. IEEE Trans. Cybern. 45(5): 940-954 (2015) - [j58]Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang:
Rating Knowledge Sharing in Cross-Domain Collaborative Filtering. IEEE Trans. Cybern. 45(5): 1054-1068 (2015) - [j57]Peng Zhang, Chuan Zhou, Peng Wang, Byron J. Gao, Xingquan Zhu, Li Guo:
E-Tree: An Efficient Indexing Structure for Ensemble Models on Data Streams. IEEE Trans. Knowl. Data Eng. 27(2): 461-474 (2015) - [j56]Meng Fang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs. IEEE Trans. Knowl. Data Eng. 27(9): 2536-2549 (2015) - [j55]Shirui Pan, Jia Wu, Xingquan Zhu:
CogBoost: Boosting for Fast Cost-Sensitive Graph Classification. IEEE Trans. Knowl. Data Eng. 27(11): 2933-2946 (2015) - 2014
- [j54]Guohua Liang, Xingquan Zhu, Chengqi Zhang:
The effect of varying levels of class distribution on bagging for different algorithms: An empirical study. Int. J. Mach. Learn. Cybern. 5(1): 63-71 (2014) - [j53]Meng Fang, Xingquan Zhu:
Active learning with uncertain labeling knowledge. Pattern Recognit. Lett. 43: 98-108 (2014) - [j52]Xindong Wu, Xingquan Zhu, Gong-Qing Wu, Wei Ding:
Data Mining with Big Data. IEEE Trans. Knowl. Data Eng. 26(1): 97-107 (2014) - [j51]Yifan Fu, Bin Li, Xingquan Zhu, Chengqi Zhang:
Active Learning without Knowing Individual Instance Labels: A Pairwise Label Homogeneity Query Approach. IEEE Trans. Knowl. Data Eng. 26(4): 808-822 (2014) - [j50]Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Bag Constrained Structure Pattern Mining for Multi-Graph Classification. IEEE Trans. Knowl. Data Eng. 26(10): 2382-2396 (2014) - 2013
- [j49]Xindong Wu, Xingquan Zhu, Yu He, Abdullah N. Arslan:
PMBC: Pattern mining from biological sequences with wildcard constraints. Comput. Biol. Medicine 43(5): 481-492 (2013) - [j48]Xingquan Zhu, Taghi M. Khoshgoftaar:
Editorial. Int. J. Artif. Intell. Tools 22(5) (2013) - [j47]Yifan Fu, Xingquan Zhu, Bin Li:
A survey on instance selection for active learning. Knowl. Inf. Syst. 35(2): 249-283 (2013) - [j46]Xindong Wu, Kui Yu, Wei Ding, Hao Wang, Xingquan Zhu:
Online Feature Selection with Streaming Features. IEEE Trans. Pattern Anal. Mach. Intell. 35(5): 1178-1192 (2013) - [j45]Yifan Fu, Xingquan Zhu, Ahmed K. Elmagarmid:
Active Learning With Optimal Instance Subset Selection. IEEE Trans. Cybern. 43(2): 464-475 (2013) - [j44]Hanning Yuan, Meng Fang, Xingquan Zhu:
Hierarchical Sampling for Multi-Instance Ensemble Learning. IEEE Trans. Knowl. Data Eng. 25(12): 2900-2905 (2013) - [j43]Bin Li, Ling Chen, Xingquan Zhu, Chengqi Zhang:
Noisy but non-malicious user detection in social recommender systems. World Wide Web 16(5-6): 677-699 (2013) - 2012
- [j42]Zhenfeng Zhu, Xingquan Zhu, Yue-Fei Guo, Yangdong Ye, Xiangyang Xue:
Inverse matrix-free incremental proximal support vector machine. Decis. Support Syst. 53(3): 395-405 (2012) - [j41]Xingquan Zhu:
Special issue on data mining applications and case study. Neurocomputing 92: 1-2 (2012) - 2011
- [j40]Dan He, Xingquan Zhu, Xindong Wu:
Mining Approximate Repeating Patterns from Sequence Data with Gap Constraints. Comput. Intell. 27(3): 336-362 (2011) - [j39]Peng Zhang, Xingquan Zhu, Yong Shi, Li Guo, Xindong Wu:
Robust ensemble learning for mining noisy data streams. Decis. Support Syst. 50(2): 469-479 (2011) - [j38]Xingquan Zhu, Bin Li, Xindong Wu, Dan He, Chengqi Zhang:
CLAP: Collaborative pattern mining for distributed information systems. Decis. Support Syst. 52(1): 40-51 (2011) - [j37]Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bond:
Corrective classification: Learning from data imperfections with aggressive and diverse classifier ensembling. Inf. Syst. 36(8): 1135-1157 (2011) - [j36]DongHong Sun, Li Liu, Peng Zhang, Xingquan Zhu, Yong Shi:
Decision Rule Extraction for Regularized Multiple Criteria Linear Programming Model. Int. J. Data Warehous. Min. 7(3): 88-101 (2011) - [j35]Xingquan Zhu, Wei Ding, Philip S. Yu, Chengqi Zhang:
One-class learning and concept summarization for data streams. Knowl. Inf. Syst. 28(3): 523-553 (2011) - [j34]Xingquan Zhu:
Cross-Domain Semi-Supervised Learning Using Feature Formulation. IEEE Trans. Syst. Man Cybern. Part B 41(6): 1627-1638 (2011) - 2010
- [j33]Zhenfeng Zhu, Yue-Fei Guo, Xingquan Zhu, Xiangyang Xue:
Normalized dimensionality reduction using nonnegative matrix factorization. Neurocomputing 73(10-12): 1783-1793 (2010) - [j32]Abu H. M. Kamal, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu, Ramaswamy Narayanan:
Feature Selection for Datasets with Imbalanced Class Distributions. Int. J. Softw. Eng. Knowl. Eng. 20(2): 113-137 (2010) - [j31]Xingquan Zhu, Peng Zhang, Xiaodong Lin, Yong Shi:
Active Learning From Stream Data Using Optimal Weight Classifier Ensemble. IEEE Trans. Syst. Man Cybern. Part B 40(6): 1607-1621 (2010) - [j30]Peng Zhang, Xingquan Zhu, Zhiwang Zhang, Yong Shi:
Multiple criteria programming models for VIP E-Mail behavior analysis. Web Intell. Agent Syst. 8(1): 69-78 (2010) - 2009
- [j29]Xindong Wu, Xingquan Zhu, Qijun Chen, Fei-Yue Wang:
Ubiquitous Mining with Interactive Data Mining Agents. J. Comput. Sci. Technol. 24(6): 1018-1027 (2009) - [j28]Xuxian Jiang, Xingquan Zhu:
vEye: behavioral footprinting for self-propagating worm detection and profiling. Knowl. Inf. Syst. 18(2): 231-262 (2009) - 2008
- [j27]Ying Yang, Xindong Wu, Xingquan Zhu:
Conceptual equivalence for contrast mining in classification learning. Data Knowl. Eng. 67(3): 413-429 (2008) - [j26]Xingquan Zhu, Chengqi Zhang, David L. Olson:
Editorial. Int. J. Softw. Informatics 2(2): 89-93 (2008) - [j25]Xingquan Zhu, Ying Yang:
A lazy bagging approach to classification. Pattern Recognit. 41(10): 2980-2992 (2008) - [j24]Xingquan Zhu, Ruoming Jin, Yuri Breitbart, Gagan Agrawal:
MMIS07, 08: mining multiple information sources workshop report. SIGKDD Explor. 10(2): 61-65 (2008) - [j23]Xindong Wu, Xingquan Zhu:
Mining With Noise Knowledge: Error-Aware Data Mining. IEEE Trans. Syst. Man Cybern. Part A 38(4): 917-932 (2008) - 2007
- [j22]Guojun Mao, Xindong Wu, Xingquan Zhu, Gong Chen, Chunnian Liu:
Mining maximal frequent itemsets from data streams. J. Inf. Sci. 33(3): 251-262 (2007) - [j21]Xingquan Zhu, Taghi M. Khoshgoftaar, Ian Davidson, Shichao Zhang:
Editorial: Special issue on mining low-quality data. Knowl. Inf. Syst. 11(2): 131-136 (2007) - [j20]Gong Chen, Xindong Wu, Xingquan Zhu:
Mining Sequential Patterns across Time Sequences. New Gener. Comput. 26(1): 75-96 (2007) - 2006
- [j19]Xingquan Zhu, Xindong Wu, Qijun Chen:
Bridging Local and Global Data Cleansing: Identifying Class Noise in Large, Distributed Data Datasets. Data Min. Knowl. Discov. 12(2-3): 275-308 (2006) - [j18]Ying Yang, Xindong Wu, Xingquan Zhu:
Mining in Anticipation for Concept Change: Proactive-Reactive Prediction in Data Streams. Data Min. Knowl. Discov. 13(3): 261-289 (2006) - [j17]Xingquan Zhu, Xindong Wu, Ying Yang:
Effective classification of noisy data streams with attribute-oriented dynamic classifier selection. Knowl. Inf. Syst. 9(3): 339-363 (2006) - [j16]Gong Chen, Xindong Wu, Xingquan Zhu, Abdullah N. Arslan, Yu He:
Efficient string matching with wildcards and length constraints. Knowl. Inf. Syst. 10(4): 399-419 (2006) - [j15]Xingquan Zhu, Xindong Wu:
Class Noise Handling for Effective Cost-Sensitive Learning by Cost-Guided Iterative Classification Filtering. IEEE Trans. Knowl. Data Eng. 18(10): 1435-1440 (2006) - 2005
- [j14]Xingquan Zhu, Xindong Wu, Ahmed K. Elmagarmid, Zhe Feng, Lide Wu:
Video Data Mining: Semantic Indexing and Event Detection from the Association Perspective. IEEE Trans. Knowl. Data Eng. 17(5): 665-677 (2005) - [j13]Xingquan Zhu, Xindong Wu:
Cost-Constrained Data Acquisition for Intelligent Data Preparation. IEEE Trans. Knowl. Data Eng. 17(11): 1542-1556 (2005) - [j12]Xingquan Zhu, Ahmed K. Elmagarmid, Xiangyang Xue, Lide Wu, Ann Christine Catlin:
InsightVideo: toward hierarchical video content organization for efficient browsing, summarization and retrieval. IEEE Trans. Multim. 7(4): 648-666 (2005) - 2004
- [j11]Xingquan Zhu, Xindong Wu:
Class Noise vs. Attribute Noise: A Quantitative Study. Artif. Intell. Rev. 22(3): 177-210 (2004) - [j10]Walid G. Aref, Ann Christine Catlin, Ahmed K. Elmagarmid, Jianping Fan, Moustafa A. Hammad, Ihab F. Ilyas, Mirette S. Marzouk, Sunil Prabhakar, Yi-Cheng Tu, Xingquan Zhu:
VDBMS: A testbed facility for research in video database benchmarking. Multim. Syst. 9(6): 575-585 (2004) - [j9]Xingquan Zhu, Xindong Wu, Jianping Fan, Ahmed K. Elmagarmid, Walid G. Aref:
Exploring video content structure for hierarchical summarization. Multim. Syst. 10(2): 98-115 (2004) - [j8]Jianping Fan, Ahmed K. Elmagarmid, Xingquan Zhu, Walid G. Aref, Lide Wu:
ClassView: hierarchical video shot classification, indexing, and accessing. IEEE Trans. Multim. 6(1): 70-86 (2004) - 2003
- [j7]Xingquan Zhu, Jianping Fan, Ahmed K. Elmagarmid, Xindong Wu:
Hierarchical video content description and summarization using unified semantic and visual similarity. Multim. Syst. 9(1): 31-53 (2003) - [j6]Jianping Fan, Xingquan Zhu, Kayvan Najarian, Lide Wu:
Accessing Video Contents through Key Objects over IP. Multim. Tools Appl. 21(1): 75-96 (2003) - [j5]Elisa Bertino, Jianping Fan, Elena Ferrari, Mohand-Said Hacid, Ahmed K. Elmagarmid, Xingquan Zhu:
A hierarchical access control model for video database systems. ACM Trans. Inf. Syst. 21(2): 155-191 (2003) - 2002
- [j4]Jianping Fan, Xingquan Zhu, Mohand-Said Hacid, Ahmed K. Elmagarmid:
Model-Based Video Classification toward Hierarchical Representation, Indexing and Access. Multim. Tools Appl. 17(1): 97-120 (2002) - 2001
- [j3]Xingquan Zhu, HongJiang Zhang, Liu Wenyin, Chunhui Hu, Lide Wu:
New query refinement and semantics integrated image retrieval system with semiautomatic annotation scheme. J. Electronic Imaging 10(4): 850-860 (2001) - [j2]Jianping Fan, Walid G. Aref, Ahmed K. Elmagarmid, Mohand-Said Hacid, Mirette S. Marzouk, Xingquan Zhu:
MultiView: Multilevel video content representation and retrieval. J. Electronic Imaging 10(4): 895-908 (2001) - [j1]Jianping Fan, Xingquan Zhu, Lide Wu:
Automatic model-based semantic object extraction algorithm. IEEE Trans. Circuits Syst. Video Technol. 11(10): 1073-1084 (2001)
Conference and Workshop Papers
- 2024
- [c180]Yufei Jin, Richard Gao, Yi He, Xingquan Zhu:
GLDL: Graph Label Distribution Learning. AAAI 2024: 12965-12974 - 2023
- [c179]Xindong Wu, Xingquan Zhu, Elena Baralis, Ruqian Lu, Vipin Kumar, Leszek Rutkowski, Jie Tang:
On Computing Paradigms - Where Will Large Language Models Be Going. ICDM 2023: 1577-1582 - [c178]Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan:
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data. NeurIPS 2023 - [c177]Boyu Li, Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen:
ConGCN: Factorized Graph Convolutional Networks for Consensus Recommendation. ECML/PKDD (4) 2023: 369-386 - [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
- [c175]Man Wu, Xingquan Zhu:
Temporal Adaptive Aggregation Network for Dynamic Graph Learning. IEEE Big Data 2022: 806-811 - [c174]Yufei Jin, Xingquan Zhu:
Predictive Masking for Semi-Supervised Graph Contrastive Learning. IEEE 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 - 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 - 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 - 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 - 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 - 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: 321-324 - [c141]Chun Wang, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang:
MGAE: Marginalized Graph Autoencoder for Graph Clustering. CIKM 2017: 889-898 - [c140]Eric Golinko, Thomas Sonderman, Xingquan Zhu:
CNFL: Categorical to Numerical Feature Learning for Clustering and Classification. DSC 2017: 585-594 - [c139]Bozhong Liu, Ling Chen, Xingquan Zhu, Ying Zhang, Chengqi Zhang, Weidong Qiu:
Protecting Location Privacy in Spatial Crowdsourcing using Encrypted Data. EDBT 2017: 478-481 - [c138]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
User Profile Preserving Social Network Embedding. IJCAI 2017: 3378-3384 - [c137]Xingquan Zhu, Jose Hurtado, Haicheng Tao:
Localized sampling for hospital re-admission prediction with imbalanced sample distributions. IJCNN 2017: 4571-4578 - [c136]Christopher Baechle, Ankur Agarwal, Ravi S. Behara, Xingquan Zhu:
Latent topic ensemble learning for hospital readmission cost reduction. IJCNN 2017: 4594-4601 - [c135]Eric Golinko, Xingquan Zhu:
GFEL: Generalized Feature Embedding Learning Using Weighted Instance Matching. IRI 2017: 235-244 - [c134]Hui Liu, Xingquan Zhu, Kristopher Kalish, Jeremy Kayne:
ULTR-CTR: Fast Page Grouping Using URL Truncation for Real-Time Click Through Rate Estimation. IRI 2017: 444-451 - 2016
- [c133]Jia Wu, Shirui Pan, Peng Zhang, Xingquan Zhu:
Direct Discriminative Bag Mapping for Multi-Instance Learning. AAAI 2016: 4274-4275 - [c132]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks. CIKM 2016: 1563-1572 - [c131]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Joint structure feature exploration and regularization for multi-task graph classification. ICDE 2016: 1474-1475 - [c130]Meng Fang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
TrGraph: Cross-network transfer learning via common signature subgraphs. ICDE 2016: 1534-1535 - [c129]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Homophily, Structure, and Content Augmented Network Representation Learning. ICDM 2016: 609-618 - [c128]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Yang Wang:
Tri-Party Deep Network Representation. IJCAI 2016: 1895-1901 - [c127]Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu:
Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness. IJCAI 2016: 2167-2173 - [c126]Ruiqi Hu, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang, Chengqi Zhang:
Co-clustering enterprise social networks. IJCNN 2016: 107-114 - [c125]Charles Wheelus, Elias Bou-Harb, Xingquan Zhu:
Towards a Big Data Architecture for Facilitating Cyber Threat Intelligence. NTMS 2016: 1-5 - 2015
- [c124]Yifan Fu, Junbin Gao, Xingquan Zhu:
Active Class Discovery by Querying Pairwise Label Homogeneity. ICDS 2015: 135-140 - [c123]Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-Graph-View Learning for Complicated Object Classification. IJCAI 2015: 3953-3959 - [c122]Michael Crawford, Xingquan Zhu:
Gender Prediction in Random Chat Networks Using Topological Network Structures and Masked Content. IRI 2015: 174-181 - [c121]Jose Hurtado, Shihong Huang, Xingquan Zhu:
Topic Discovery and Future Trend Prediction Using Association Analysis and Ensemble Forecasting. IRI 2015: 203-206 - [c120]Isabel Casas, Jose Hurtado, Xingquan Zhu:
Social Network Privacy: Issues and Measurement. WISE (2) 2015: 488-502 - 2014
- [c119]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning. CIKM 2014: 1699-1708 - [c118]Ting Guo, Xingquan Zhu, Jian Pei, Chengqi Zhang:
SNOC: Streaming Network Node Classification. ICDM 2014: 150-159 - [c117]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-graph-view Learning for Graph Classification. ICDM 2014: 590-599 - [c116]Fei Xie, Xindong Wu, Xingquan Zhu:
Document-Specific Keyphrase Extraction Using Sequential Patterns with Wildcards. ICDM 2014: 1055-1060 - [c115]Jia Wu, Shirui Pan, Zhihua Cai, Xingquan Zhu, Chengqi Zhang:
Dual instance and attribute weighting for Naive Bayes classification. IJCNN 2014: 1675-1679 - [c114]Jia Wu, Zhihua Cai, Shirui Pan, Xingquan Zhu, Chengqi Zhang:
Attribute weighting: How and when does it work for Bayesian Network Classification. IJCNN 2014: 4076-4083 - [c113]Hamzah Al Najada, Xingquan Zhu:
iSRD: Spam review detection with imbalanced data distributions. IRI 2014: 553-560 - [c112]Jose Hurtado, Napat Taweewitchakreeya, Xingquan Zhu:
Who wrote this paper? Learning for authorship de-identification using stylometric featuress. IRI 2014: 859-862 - [c111]Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-Instance Learning from Positive and Unlabeled Bags. PAKDD (1) 2014: 237-248 - [c110]Ting Guo, Xingquan Zhu:
Super-Graph Classification. PAKDD (1) 2014: 323-336 - [c109]Lianhua Chi, Bin Li, Xingquan Zhu:
Context-Preserving Hashing for Fast Text Classification. SDM 2014: 100-108 - [c108]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-Graph Learning with Positive and Unlabeled Bags. SDM 2014: 217-225 - 2013
- [c107]Ting Guo, Xingquan Zhu:
Understanding the roles of sub-graph features for graph classification: an empirical study perspective. CIKM 2013: 817-822 - [c106]Meng Fang, Jie Yin, Xingquan Zhu:
Active exploration: simultaneous sampling and labeling for large graphs. CIKM 2013: 829-834 - [c105]Ting Guo, Lianhua Chi, Xingquan Zhu:
Graph hashing and factorization for fast graph stream classification. CIKM 2013: 1607-1612 - [c104]Shirui Pan, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Graph stream classification using labeled and unlabeled graphs. ICDE 2013: 398-409 - [c103]Meng Fang, Jie Yin, Xingquan Zhu:
Transfer Learning across Networks for Collective Classification. ICDM 2013: 161-170 - [c102]Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-instance Multi-graph Dual Embedding Learning. ICDM 2013: 827-836 - [c101]Chuan Zhou, Peng Zhang, Jing Guo, Xingquan Zhu, Li Guo:
UBLF: An Upper Bound Based Approach to Discover Influential Nodes in Social Networks. ICDM 2013: 907-916 - [c100]Jose Hurtado, Napat Taweewitchakreeya, Xue Kong, Xingquan Zhu:
A Classifier Ensembling Approach for Imbalanced Social Link Prediction. ICMLA (1) 2013: 436-439 - [c99]Matthew Herland, Pablo Pastran, Xingquan Zhu:
An Empirical Study of Robustness of Network Centrality Scores in Various Networks and Conditions. ICTAI 2013: 221-228 - [c98]Naser Peiravian, Xingquan Zhu:
Machine Learning for Android Malware Detection Using Permission and API Calls. ICTAI 2013: 300-305 - [c97]Shirui Pan, Xingquan Zhu:
Graph Classification with Imbalanced Class Distributions and Noise. IJCAI 2013: 1586-1592 - [c96]Jia Wu, Zhihua Cai, Xingquan Zhu:
Self-adaptive probability estimation for Naive Bayes classification. IJCNN 2013: 1-8 - [c95]Jia Wu, Zhihua Cai, Sanyou Zeng, Xingquan Zhu:
Artificial immune system for attribute weighted Naive Bayes classification. IJCNN 2013: 1-8 - [c94]Anand Kumar, Xingquan Zhu, Yi-Cheng Tu, Sagar Pandit:
Compression in Molecular Simulation Datasets. IScIDE 2013: 22-29 - [c93]Lianhua Chi, Bin Li, Xingquan Zhu:
Fast Graph Stream Classification Using Discriminative Clique Hashing. PAKDD (1) 2013: 225-236 - [c92]Meng Fang, Jie Yin, Xingquan Zhu:
Knowledge Transfer for Multi-labeler Active Learning. ECML/PKDD (1) 2013: 273-288 - [c91]Meng Fang, Jie Yin, Chengqi Zhang, Xingquan Zhu:
Active Class Discovery and Learning for Networked Data. SDM 2013: 315-323 - 2012
- [c90]Meng Fang, Xingquan Zhu, Chengqi Zhang:
Active Learning from Oracle with Knowledge Blind Spot. AAAI 2012: 2421-2422 - [c89]Buyun Qu, Zhibin Zhang, Le Guo, Xingquan Zhu, Li Guo, Dan Meng:
An empirical study of morphing on network traffic classification. CHINACOM 2012: 227-232 - [c88]Guodong Long, Ling Chen, Xingquan Zhu, Chengqi Zhang:
TCSST: transfer classification of short & sparse text using external data. CIKM 2012: 764-772 - [c87]Shirui Pan, Xingquan Zhu:
CGStream: continuous correlated graph query for data streams. CIKM 2012: 1183-1192 - [c86]Zhenfeng Zhu, Xingquan Zhu, Yangdong Ye, Yue-Fei Guo, Xiangyang Xue:
Parallel proximal support vector machine for high-dimensional pattern classification. CIKM 2012: 2351-2354 - [c85]Shirui Pan, Xingquan Zhu:
Continuous top-k query for graph streams. CIKM 2012: 2659-2662 - [c84]Bin Li, Xingquan Zhu, Lianhua Chi, Chengqi Zhang:
Nested Subtree Hash Kernels for Large-Scale Graph Classification over Streams. ICDM 2012: 399-408 - [c83]Meng Fang, Xingquan Zhu, Bin Li, Wei Ding, Xindong Wu:
Self-Taught Active Learning from Crowds. ICDM 2012: 858-863 - [c82]Meng Fang, Xingquan Zhu:
I don't know the label: Active learning with blind knowledge. ICPR 2012: 2238-2241 - [c81]Shirui Pan, Xingquan Zhu, Meng Fang:
Top-k correlated subgraph query for data streams. ICPR 2012: 2906-2909 - 2011
- [c80]Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, Xingquan Zhu:
Tracking User-Preference Varying Speed in Collaborative Filtering. AAAI 2011: 133-138 - [c79]Yifan Fu, Xingquan Zhu:
Optimal Subset Selection for Active Learning. AAAI 2011: 1776-1777 - [c78]Ting Guo, Zhanshan Li, Ruizhi Guo, Xingquan Zhu:
Large Scale Diagnosis Using Associations between System Outputs and Components. AAAI 2011: 1786-1787 - [c77]Guohua Liang, Xingquan Zhu, Chengqi Zhang:
An Empirical Study of Bagging Predictors for Different Learning Algorithms. AAAI 2011: 1802-1803 - [c76]Guohua Liang, Xingquan Zhu, Chengqi Zhang:
An Empirical Study of Bagging Predictors for Imbalanced Data with Different Levels of Class Distribution. Australasian Conference on Artificial Intelligence 2011: 213-222 - [c75]Yifan Fu, Bin Li, Xingquan Zhu, Chengqi Zhang:
Do they belong to the same class: active learning by querying pairwise label homogeneity. CIKM 2011: 2161-2164 - [c74]Zhenfeng Zhu, Xingquan Zhu, Yangdong Ye, Yue-Fei Guo, Xiangyang Xue:
Transfer active learning. CIKM 2011: 2169-2172 - [c73]Peng Zhang, Byron J. Gao, Xingquan Zhu, Li Guo:
Enabling Fast Lazy Learning for Data Streams. ICDM 2011: 932-941 - [c72]Dan He, Xingquan Zhu, Douglas Stott Parker Jr.:
How Does Research Evolve? Pattern Mining for Research Meme Cycles. ICDM 2011: 1068-1073 - [c71]Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, Xindong Wu:
Cross-Domain Collaborative Filtering over Time. IJCAI 2011: 2293-2298 - [c70]Peng Zhang, Jun Li, Peng Wang, Byron J. Gao, Xingquan Zhu, Li Guo:
Enabling fast prediction for ensemble models on data streams. KDD 2011: 177-185 - [c69]Hui Wu, Guangzhi Qu, Xingquan Zhu:
Self-adjust Local Connectivity Analysis for Spectral Clustering. PAKDD (1) 2011: 209-224 - 2010
- [c68]Zhenfeng Zhu, Xingquan Zhu, Yue-Fei Guo, Xiangyang Xue:
Transfer incremental learning for pattern classification. CIKM 2010: 1709-1712 - [c67]Peng Zhang, Xingquan Zhu, Jianlong Tan, Li Guo:
SKIF: a data imputation framework for concept drifting data streams. CIKM 2010: 1869-1872 - [c66]Peng Zhang, Xingquan Zhu, Jianlong Tan, Li Guo:
Classifier and Cluster Ensembles for Mining Concept Drifting Data Streams. ICDM 2010: 1175-1180 - [c65]Zhenyu Lu, Xindong Wu, Xingquan Zhu, Josh C. Bongard:
Ensemble pruning via individual contribution ordering. KDD 2010: 871-880 - [c64]Dan He, Xindong Wu, Xingquan Zhu:
Rule Synthesizing from Multiple Related Databases. PAKDD (2) 2010: 201-213 - 2009
- [c63]Abu H. M. Kamal, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu, Muhammad Shoaib:
The Impact of Gene Selection on Imbalanced Microarray Expression Data. BICoB 2009: 259-269 - [c62]Michael Slavik, Xingquan Zhu, Imad Mahgoub, Muhammad Shoaib:
Parallel Selection of Informative Genes for Classification. BICoB 2009: 388-399 - [c61]Peng Zhang, Xingquan Zhu, Yong Shi:
Bias-Variance Analysis for Ensembling Regularized Multiple Criteria Linear Programming Models. ICCS (2) 2009: 524-533 - [c60]Peng Zhang, Xingquan Zhu, Li Guo:
Mining Data Streams with Labeled and Unlabeled Training Examples. ICDM 2009: 627-636 - [c59]Xingquan Zhu, Xindong Wu, Chengqi Zhang:
Vague One-Class Learning for Data Streams. ICDM 2009: 657-666 - [c58]Dan He, Xingquan Zhu, Xindong Wu:
Approximate Repeating Pattern Mining with Gap Requirements. ICTAI 2009: 17-24 - [c57]Dan He, Xingquan Zhu, Xindong Wu:
Error Detection and Uncertainty Modeling for Imprecise Data. ICTAI 2009: 792-795 - [c56]Xingquan Zhu, Ruoming Jin:
Multiple Information Sources Cooperative Learning. IJCAI 2009: 1369-1376 - [c55]Abu H. M. Kamal, Xingquan Zhu, Ramaswamy Narayanan:
Gene Selection for Microarray Expression Data with Imbalanced Sample Distributions. IJCBS 2009: 3-9 - [c54]Abu H. M. Kamal, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu:
Feature Selection with biased Sample Distributions. IRI 2009: 23-28 - [c53]Peng Zhang, Xingquan Zhu, Yong Shi, Xindong Wu:
An Aggregate Ensemble for Mining Concept Drifting Data Streams with Noise. PAKDD 2009: 1021-1029 - 2008
- [c52]Chinar C. Shah, Xingquan Zhu, Taghi M. Khoshgoftaar, Justin Beyer:
Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction. FLAIRS 2008: 95-100 - [c51]Peng Zhang, Yingjie Tian, Zhiwang Zhang, Aihua Li, Xingquan Zhu:
Select Objective Functions for Multiple Criteria Programming Classification. Web Intelligence/IAT Workshops 2008: 420-423 - [c50]Xingquan Zhu, Peng Zhang, Xindong Wu, Dan He, Chengqi Zhang, Yong Shi:
Cleansing Noisy Data Streams. ICDM 2008: 1139-1144 - [c49]Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu:
VoB predictors: Voting on bagging classifications. ICPR 2008: 1-4 - [c48]Xingquan Zhu, Chengyi Bao, Weidong Qiu:
Bagging very weak learners with lazy local learning. ICPR 2008: 1-4 - [c47]Abu H. M. Kamal, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu, Yong Shi:
An empirical study of supervised learning for biological sequence profiling and microarray expression data analysis. IRI 2008: 70-75 - [c46]Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu:
VCI predictors: Voting on classifications from imputed learning sets. IRI 2008: 296-301 - [c45]Peng Zhang, Xingquan Zhu, Yong Shi:
Categorizing and mining concept drifting data streams. KDD 2008: 812-820 - [c44]Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Russell Greiner:
Imputation-boosted collaborative filtering using machine learning classifiers. SAC 2008: 949-950 - [c43]Yongsuk Lee, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu:
iVESTA: an interactive visualization and evaluation system for drive test data. SAC 2008: 1953-1957 - 2007
- [c42]Dan He, Xindong Wu, Xingquan Zhu:
SAIL-APPROX: An Efficient On-Line Algorithm for Approximate Pattern Matching with Wildcards and Length Constraints. BIBM 2007: 151-158 - [c41]Jing Wang, Ying Liu, Lin Zhou, Yong Shi, Xingquan Zhu:
Pushing Frequency Constraint to Utility Mining Model. International Conference on Computational Science (3) 2007: 685-692 - [c40]Ying Liu, Peter Scheuermann, Xingsen Li, Xingquan Zhu:
Using WordNet to Disambiguate Word Senses for Text Classification. International Conference on Computational Science (3) 2007: 781-789 - [c39]Xingquan Zhu, Xindong Wu:
Discovering Relational Patterns across Multiple Databases. ICDE 2007: 726-735 - [c38]Xingquan Zhu, Peng Zhang, Xiaodong Lin, Yong Shi:
Active Learning from Data Streams. ICDM 2007: 757-762 - [c37]Xingquan Zhu:
Lazy Bagging for Classifying Imbalanced Data. ICDM 2007: 763-768 - [c36]Xingquan Zhu, Xindong Wu, Taghi M. Khoshgoftaar, Yong Shi:
An Empirical Study of the Noise Impact on Cost-Sensitive Learning. IJCAI 2007: 1168-1174 - [c35]Xingquan Zhu, Xindong Wu:
Mining Complex Patterns across Sequences with Gap Requirements. IJCAI 2007: 2934-2941 - [c34]Yu He, Xindong Wu, Xingquan Zhu, Abdullah N. Arslan:
Mining Frequent Patterns with Wildcards from Biological Sequences. IRI 2007: 329-334 - [c33]Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Andres Folleco:
Rule-Based Multiple Object Tracking for Traffic Surveillance Using Collaborative Background Extraction. ISVC (2) 2007: 469-478 - [c32]Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Xingquan Zhu:
Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts. Web Intelligence 2007: 645-649 - 2006
- [c31]Xianhua Jiang, Yuichi Motai, Robert R. Snapp, Xingquan Zhu:
Accelerated Kernel Feature Analysis. CVPR (1) 2006: 109-116 - [c30]Xingquan Zhu, Xindong Wu:
Error awareness data mining. GrC 2006: 269-274 - [c29]Yan Zhang, Xingquan Zhu, Xindong Wu:
Corrective Classification: Classifier Ensembling with Corrective and Diverse Base Learners. ICDM 2006: 1199-1204 - [c28]Xingquan Zhu, Xindong Wu:
Scalable Representative Instance Selection and Ranking. ICPR (3) 2006: 352-355 - 2005
- [c27]Gong Chen, Xindong Wu, Xingquan Zhu:
Sequential Pattern Mining in Multiple Streams. ICDM 2005: 585-588 - [c26]Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bond:
ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing. ICTAI 2005: 310-317 - [c25]Qijun Chen, Xindong Wu, Xingquan Zhu:
Scalable Inductive Learning on Partitioned Data. ISMIS 2005: 391-403 - [c24]Ying Yang, Xindong Wu, Xingquan Zhu:
Combining proactive and reactive predictions for data streams. KDD 2005: 710-715 - 2004
- [c23]Xingquan Zhu, Xindong Wu, Ying Yang:
Error Detection and Impact-Sensitive Instance Ranking in Noisy Datasets. AAAI 2004: 378-384 - [c22]Xingquan Zhu, Xindong Wu:
Cost-Guided Class Noise Handling for Effective Cost-Sensitive Learning. ICDM 2004: 297-304 - [c21]Xingquan Zhu, Xindong Wu, Ying Yang:
Dynamic Classifier Selection for Effective Mining from Noisy Data Streams. ICDM 2004: 305-312 - [c20]Xingquan Zhu, Xindong Wu:
Data Acquisition with Active and Impact-Sensitive Instance Selection. ICTAI 2004: 721-726 - [c19]Qijun Chen, Xindong Wu, Xingquan Zhu:
OIDM: Online Interactive Data Mining. IEA/AIE 2004: 66-76 - [c18]Ying Yang, Xindong Wu, Xingquan Zhu:
Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources. PKDD 2004: 471-483 - 2003
- [c17]Xingquan Zhu, Walid G. Aref, Jianping Fan, Ann Christine Catlin, Ahmed K. Elmagarmid:
Medical Video Mining for Efficient Database Indexing, Management and Access. ICDE 2003: 569-580 - [c16]Hangzai Luo, Jianping Fan, Jing Xiao, Xingquan Zhu:
Semantic principal video shot classification via mixture Gaussian. ICME 2003: 189-192 - [c15]Xingquan Zhu, Xindong Wu:
Sequential association mining for video summarization. ICME 2003: 333-336 - [c14]Xingquan Zhu, Xindong Wu, Qijun Chen:
Eliminating Class Noise in Large Datasets. ICML 2003: 920-927 - [c13]Xingquan Zhu, Xindong Wu:
Mining Video Associations for Efficient Database Management. IJCAI 2003: 1422- - 2002
- [c12]Xingquan Zhu, Jianping Fan, Walid G. Aref, Ahmed K. Elmagarmid:
ClassMiner: Mining Medical Video Content Structure and Events Towards Efficient Access and Scalable Skimming. DMKD 2002 - [c11]Walid G. Aref, Ann Christine Catlin, Ahmed K. Elmagarmid, Jianping Fan, J. Guo, Moustafa A. Hammad, Ihab F. Ilyas, Mirette S. Marzouk, Sunil Prabhakar, Abdelmounaam Rezgui, S. Teoh, Evimaria Terzi, Yi-Cheng Tu, Athena Vakali, Xingquan Zhu:
A Distributed Database Server for Continuous Media. ICDE 2002: 490-491 - [c10]Xingquan Zhu, Jianping Fan, Ahmed K. Elmagarmid:
Towards facial feature extraction and verification for omni-face detection in video/images. ICIP (2) 2002: 113-116 - [c9]Walid G. Aref, Ann Christine Catlin, Jianping Fan, Ahmed K. Elmagarmid, Moustafa A. Hammad, Ihab F. Ilyas, Mirette S. Marzouk, Xingquan Zhu:
A Video Database Management System for Advancing Video Database Research. Multimedia Information Systems 2002: 8-17 - [c8]Xingquan Zhu, Jianping Fan, Mohand-Said Hacid, Ahmed K. Elmagarmid:
ClassMiner: mining medical video for scalable skimming and summarization. ACM Multimedia 2002: 79-80 - [c7]Xingquan Zhu, Jianping Fan, Xiangyang Xue, Lide Wu, Ahmed K. Elmagarmid:
Semi-automatic Video Content Annotation. IEEE Pacific Rim Conference on Multimedia 2002: 245-252 - [c6]Xingquan Zhu, Xiangyang Xue, Jianping Fan, Lide Wu:
Qualitative Camera Motion Classification for Content-Based Video Indexing. IEEE Pacific Rim Conference on Multimedia 2002: 1128-1136 - [c5]Jianping Fan, Mathurin Body, Xingquan Zhu, Mohand-Said Hacid, Essam A. El-Kwae:
Seeded image segmentation for content-based image retrieval application. Storage and Retrieval for Media Databases 2002: 10-21 - [c4]Xingquan Zhu, Jianping Fan, Ahmed K. Elmagarmid, Walid G. Aref:
Hierarchical video summarization for medical data. Storage and Retrieval for Media Databases 2002: 395-406 - 2001
- [c3]Jianping Fan, Xingquan Zhu, Lide Wu:
Seeded Semantic Object Generation toward Content-Based Video Indexing. IEEE Pacific Rim Conference on Multimedia 2001: 837-842 - [c2]Xingquan Zhu, Lide Wu, Xiangyang Xue, Xiaoye Lu, Jianping Fan:
Automatic Scene Detection in News Program by Integrating Visual Feature and Rules. IEEE Pacific Rim Conference on Multimedia 2001: 843-848 - 2000
- [c1]Ye Lu, Chunhui Hu, Xingquan Zhu, HongJiang Zhang, Qiang Yang:
A unified framework for semantics and feature based relevance feedback in image retrieval systems. ACM Multimedia 2000: 31-37
Parts in Books or Collections
- 2008
- [p1]Xindong Wu, Yan Zhang, Xingquan Zhu:
Data Mining. Wiley Encyclopedia of Computer Science and Engineering 2008
Editorship
- 2024
- [e6]Minh Hoàng Hà, Xingquan Zhu, My T. Thai:
Computational Data and Social Networks - 12th International Conference, CSoNet 2023, Hanoi, Vietnam, December 11-13, 2023, Proceedings. Lecture Notes in Computer Science 14479, Springer 2024, ISBN 978-981-97-0668-6 [contents] - 2022
- [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] - 2021
- [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] - 2013
- [e2]Shuliang Wang, Xingquan Zhu, Tingting He:
2013 IEEE International Conference on Granular Computing, GrC 2013, Beijing, China, December 13-15, 2013. IEEE Computer Society 2013, ISBN 978-1-4799-1282-7 [contents] - 2010
- [e1]Sorin Draghici, Taghi M. Khoshgoftaar, Vasile Palade, Witold Pedrycz, M. Arif Wani, Xingquan Zhu:
The Ninth International Conference on Machine Learning and Applications, ICMLA 2010, Washington, DC, USA, 12-14 December 2010. IEEE Computer Society 2010, ISBN 978-0-7695-4300-0 [contents]
Reference Works
- 2018
- [r2]Xingquan Zhu:
Quantitative Association Rules. Encyclopedia of Database Systems (2nd ed.) 2018 - 2009
- [r1]Xingquan Zhu:
Quantitative Association Rules. Encyclopedia of Database Systems 2009: 2240-2244
Informal and Other Publications
- 2024
- [i31]Man Wu, Xin Zheng, Qin Zhang, Xiao Shen, Xiong Luo, Xingquan Zhu, Shirui Pan:
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning. CoRR abs/2402.16374 (2024) - [i30]Youxi Wu, Zhen Wang, Yan Li, Yingchun Guo, He Jiang, Xingquan Zhu, Xindong Wu:
Co-occurrence order-preserving pattern mining. CoRR abs/2404.19243 (2024) - [i29]Yufei Jin, Xingquan Zhu:
ATNPA: A Unified View of Oversmoothing Alleviation in Graph Neural Networks. CoRR abs/2405.01663 (2024) - [i28]Zhiqiang Wang, Dejia Xu, Rana Muhammad Shahroz Khan, Yanbin Lin, Zhiwen Fan, Xingquan Zhu:
LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild. CoRR abs/2405.20363 (2024) - 2023
- [i27]Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan:
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data. CoRR abs/2306.02664 (2023) - [i26]Youxi Wu, Yufei Meng, Yan Li, Lei Guo, Xingquan Zhu, Philippe Fournier-Viger, Xindong Wu:
Top-k contrast order-preserving pattern mining for time series classification. CoRR abs/2310.02612 (2023) - [i25]Zhiqiang Wang, Yiran Pang, Cihan Ulus, Xingquan Zhu:
Counting Manatee Aggregations using Deep Neural Networks and Anisotropic Gaussian Kernel. CoRR abs/2311.02315 (2023) - [i24]Meng Geng, Youxi Wu, Yan Li, Jing Liu, Philippe Fournier-Viger, Xingquan Zhu, Xindong Wu:
Repetitive nonoverlapping sequential pattern mining. CoRR abs/2311.09667 (2023) - 2022
- [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
- [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
- [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) - 2019
- [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
- [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) - 2016
- [i2]Haishuai Wang, Jia Wu, Xingquan Zhu, Chengqi Zhang:
Time-Variant Graph Classification. CoRR abs/1609.04350 (2016) - 2014
- [i1]Meng Fang, Jie Yin, Xingquan Zhu:
Transfer Learning across Networks for Collective Classification. CoRR abs/1403.2484 (2014)
Coauthor Index
[j134] [j133] [j132] [j129] [j128] [j127] [j116] [j114] [j113] [j112] [j110] [j105] [j86] [j83] [j77] [j76] [j74] [j72] [j52] [j49] [j46] [j40] [j39] [j38] [j37] [j29] [j27] [j23] [j22] [j20] [j19] [j18] [j17] [j16] [j15] [j14] [j13] [j11] [j9] [j7] [c179] [c116] [c83] [c71] [c65] [c64] [c59] [c58] [c57] [c53] [c50] [c42] [c39] [c36] [c35] [c34] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c15] [c14] [c13] [p1] [e5] [i30] [i26] [i24] [i23] [i22] [i21]
[j103] [j98] [j95] [j92] [j88] [j84] [j83] [j82] [j78] [j75] [j74] [j73] [j72] [j69] [j68] [j66] [j64] [j62] [j59] [j58] [j56] [j54] [j51] [j50] [j43] [j38] [j35] [j26] [c148] [c144] [c139] [c138] [c132] [c131] [c130] [c129] [c128] [c126] [c123] [c119] [c118] [c117] [c115] [c114] [c111] [c108] [c104] [c102] [c91] [c90] [c88] [c84] [c77] [c76] [c75] [c71] [c59] [c50] [i10] [i9] [i5] [i4] [i3] [i2]
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