Xiangnan Kong

According to our database, Xiangnan Kong authored at least 139 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Amalgamating Multi-Task Models with Heterogeneous Architectures.

Jidapa Thadajarassiri, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks.

Thomas Hartvigsen, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner

CoRR, 2023

One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data.

Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Multi-State Brain Network Discovery.

Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong

Proceedings of the IEEE International Conference on Big Data, 2023

Multi-Item Continuous Influence Maximization.

Jianjun Luo, Ryan A. Rossi, Xiangnan Kong, Yanhua Li

Proceedings of the IEEE International Conference on Big Data, 2023

Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer.

Jidapa Thadajarassiri, Thomas Hartvigsen, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Multi-task attributed graphical lasso and its application in fund classification.

Yao Zhang, Sijia Peng, Yun Xiong, Xiangnan Kong, Xinyue Liu, Yangyong Zhu

World Wide Web, 2022

Role-Based Graph Embeddings.

Nesreen K. Ahmed, Ryan A. Rossi, John Boaz Lee, Theodore L. Willke, Rong Zhou, Xiangnan Kong, Hoda Eldardiry

IEEE Trans. Knowl. Data Eng., 2022

Off-Deployment Traffic Estimation - A Traffic Generative Adversarial Networks Approach.

Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo

IEEE Trans. Big Data, 2022

ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data.

Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration.

Yao Su, Xin Dai, Lifang He, Xiangnan Kong

Proceedings of the IEEE International Conference on Data Mining, 2022

STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation.

Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo

Proceedings of the IEEE International Conference on Data Mining, 2022

Stop&Hop: Early Classification of Irregular Time Series.

Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

IGE+: A Framework for Learning Node Embeddings in Interaction Graphs.

Yao Zhang, Yun Xiong, Xiangnan Kong, Zhuang Niu, Yangyong Zhu

IEEE Trans. Knowl. Data Eng., 2021

GraphInception: Convolutional Neural Networks for Collective Classification in Heterogeneous Information Networks.

Yun Xiong, Yizhou Zhang, Xiangnan Kong, Huidi Chen, Yangyong Zhu

IEEE Trans. Knowl. Data Eng., 2021

PieSlicer: Dynamically Improving Response Time for Cloud-based CNN Inference.

Samuel S. Ogden, Xiangnan Kong, Tian Guo

Proceedings of the ICPE '21: ACM/SPEC International Conference on Performance Engineering, 2021

CiNet: Redesigning Deep Neural Networks for Efficient Mobile-Cloud Collaborative Inference.

Xin Dai, Xiangnan Kong, Tian Guo, Yixian Huang

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks.

Hang Yin, John Boaz Lee, Xiangnan Kong, Thomas Hartvigsen, Sihong Xie

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Self-learn to Explain Siamese Networks Robustly.

Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie

Proceedings of the IEEE International Conference on Data Mining, 2021

FiShNet: Fine-Grained Filter Sharing for Resource-Efficient Multi-Task Learning.

Xin Dai, Xiangnan Kong, Tian Guo, Xinlu He

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Human-like Explanation for Text Classification With Limited Attention Supervision.

Dongyu Zhang, Cansu Sen, Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Semi-Supervised Knowledge Amalgamation for Sequence Classification.

Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks.

Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin

Inf. Process. Manag., 2020

Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions.

John Boaz Lee, Xiangnan Kong, Constance M. Moore, Nesreen K. Ahmed

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Dual-Attention Recurrent Networks for Affine Registration of Neuroimaging Data.

Xin Dai, Xiangnan Kong, Xinyue Liu, John Boaz Lee, Constance M. Moore

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks.

Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Recurrent Halting Chain for Early Multi-label Classification.

Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Recurrent Networks for Guided Multi-Attention Classification.

Xin Dai, Xiangnan Kong, Tian Guo, John Boaz Lee, Xinyue Liu, Constance M. Moore

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events.

Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Code2Text: Dual Attention Syntax Annotation Networks for Structure-Aware Code Translation.

Yun Xiong, Shaofeng Xu, Keyao Rong, Xinyue Liu, Xiangnan Kong, Shanshan Li, Philip S. Yu, Yangyong Zhu

Proceedings of the Database Systems for Advanced Applications, 2020

Learning to Selectively Update State Neurons in Recurrent Networks.

Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

EPNet: Learning to Exit with Flexible Multi-Branch Network.

Xin Dai, Xiangnan Kong, Tian Guo

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

MLAS: Metric Learning on Attributed Sequences.

Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks.

Hang Yin, Xinyue Liu, Xiangnan Kong

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Learning Similarity-Preserving Meta-Embedding for Text Mining.

Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding.

Xiao Qin, Cao Xiao, Tengfei Ma, Tabassum Kakar, Susmitha Wunnava, Xiangnan Kong, Elke A. Rundensteiner, Fei Wang

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Multi-task Attributed Graphical Lasso.

Yao Zhang, Yun Xiong, Xiangnan Kong, Xinyue Liu, Yangyong Zhu

Proceedings of the Web and Big Data - 4th International Joint Conference, 2020

Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words?

Cansu Sen, Thomas Hartvigsen, Biao Yin, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Locally Weighted Fusion of Structural and Attribute Information in Graph Clustering.

Yafang Li, Caiyan Jia, Xiangnan Kong, Liu Yang, Jian Yu

IEEE Trans. Cybern., 2019

Learning compact graph representations via an encoder-decoder network.

John Boaz Lee, Xiangnan Kong

Appl. Netw. Sci., 2019

Signed Distance-based Deep Memory Recommender.

Thanh Tran, Xinyue Liu, Kyumin Lee, Xiangnan Kong

Proceedings of the World Wide Web Conference, 2019

NetMerger: Predicting Cross-network Links in Merged Heterogeneous Networks.

Yao Zhang, Yun Xiong, Lu Ruan, Xiangnan Kong, Yangyong Zhu

Proceedings of the 2019 IEEE/WIC/ACM International Conference on Web Intelligence, 2019

AMAS: Attention Model for Attributed Sequence Classification.

Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Adaptive-Halting Policy Network for Early Classification.

Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks.

Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Net2Text: An Edge Labelling Language Model for Personalized Review Generation.

Shaofeng Xu, Yun Xiong, Xiangnan Kong, Yangyong Zhu

Proceedings of the Database Systems for Advanced Applications, 2019

Author Set Identification via Quasi-Clique Discovery.

Yuyan Zheng, Chuan Shi, Xiangnan Kong, Yanfang Ye

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Graph Convolutional Networks with Motif-based Attention.

John Boaz Lee, Ryan A. Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Attributed Sequence Embedding.

Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Learning Temporal Relevance in Longitudinal Medical Notes.

Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention.

Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining.

Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

Competitive opinion maximization in social networks.

Jianjun Luo, Xinyue Liu, Xiangnan Kong

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018

Graph Classification in Heterogeneous Networks.

Xiangnan Kong, Philip S. Yu

Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

NetCycle+: A Framework for Collective Evolution Inference in Dynamic Heterogeneous Networks.

Yun Xiong, Yizhou Zhang, Xiangnan Kong, Yangyong Zhu

IEEE Trans. Knowl. Data Eng., 2018

Higher-order Graph Convolutional Networks.

John Boaz Lee, Ryan A. Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao

CoRR, 2018

Learning Role-based Graph Embeddings.

Nesreen K. Ahmed, Ryan A. Rossi, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Rong Zhou, Hoda Eldardiry

CoRR, 2018

Deep Collective Classification in Heterogeneous Information Networks.

Yizhou Zhang, Yun Xiong, Xiangnan Kong, Shanshan Li, Jinhong Mi, Yangyong Zhu

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Bidirectional LSTM-CRF for Adverse Drug Event Tagging in Electronic Health Records.

Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Elke A. Rundensteiner, Xiangnan Kong

Proceedings of the 1st International Workshop on Medication and Adverse Drug Event Detection, 2018

Active Opinion Maximization in Social Networks.

Xinyue Liu, Xiangnan Kong, Philip S. Yu

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Graph Classification using Structural Attention.

John Boaz Lee, Ryan A. Rossi, Xiangnan Kong

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Coherent Graphical Lasso for Brain Network Discovery.

Hang Yin, Xiangnan Kong, Xinyue Liu

Proceedings of the IEEE International Conference on Data Mining, 2018

TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks.

Xinyue Liu, Xiangnan Kong, Lei Liu, Kuorong Chiang

Proceedings of the IEEE International Conference on Data Mining, 2018

Sharing Uncertain Graphs Using Syntactic Private Graph Models.

Dongqing Xiao, Mohamed Y. Eltabakh, Xiangnan Kong

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Functional-Oriented Relationship Strength Estimation: From Online Events to Offline Interactions.

Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu, Shimin Zhao, Shanshan Li

Proceedings of the Database Systems for Advanced Applications, 2018

Tracking Dynamic Magnet Communities: Insights from a Network Perspective.

Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu

Proceedings of the Database Systems for Advanced Applications, 2018

Multi-layered Learning for Information Extraction from Adverse Drug Event Narratives.

Susmitha Wunnava, Xiao Qin, Tabassum Kakar, M. L. Tlachac, Xiangnan Kong, Elke A. Rundensteiner, Sanjay K. Sahoo, Suranjan De

Proceedings of the Biomedical Engineering Systems and Technologies, 2018

One Size Does Not Fit All: An Ensemble Approach Towards Information Extraction from Adverse Drug Event Narratives.

Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke A. Rundensteiner, Sanjay K. Sahoo, Suranjan De

Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), 2018

Early Prediction of MRSA Infections using Electronic Health Records.

Thomas Hartvigsen, Cansu Sen, Sarah Brownell, Erin Teeple, Xiangnan Kong, Elke A. Rundensteiner

Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), 2018

One-Shot Learning on Attributed Sequences.

Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Aditya Arora, Jihane Zouaoui

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Predicting Disease-related Associations by Heterogeneous Network Embedding.

Yun Xiong, Lu Ruan, Mengjie Guo, Chunlei Tang, Xiangnan Kong, Yangyong Zhu, Wei Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Deep Learning Strategies for Automatic Detection of Medication and Adverse Drug Events from Electronic Health Records.

Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Elke A. Rundensteiner, Xiangnan Kong

Proceedings of the AMIA 2018, 2018

Clustering Uncertain Graphs with Node Attributes.

Yafang Li, Xiangnan Kong, Caiyan Jia, Jianqiang Li

Proceedings of The 10th Asian Conference on Machine Learning, 2018

2017

Discover trends in public emotion using social sensing.

Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu

SIGWEB Newsl., 2017

Representation Learning in Large Attributed Graphs.

Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Hoda Eldardiry

CoRR, 2017

Deep Graph Attention Model.

John Boaz Lee, Ryan A. Rossi, Xiangnan Kong

CoRR, 2017

A Framework for Generalizing Graph-based Representation Learning Methods.

Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Hoda Eldardiry

CoRR, 2017

Using Social Sensing to Discover Trends in Public Emotion.

Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu

Proceedings of the 11th IEEE International Conference on Semantic Computing, 2017

Meta-Path Graphical Lasso for Learning Heterogeneous Connectivities.

Yao Zhang, Yun Xiong, Xinyue Liu, Xiangnan Kong, Yangyong Zhu

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Unified and Contrasting Graphical Lasso for Brain Network Discovery.

Xinyue Liu, Xiangnan Kong, Ann B. Ragin

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Identifying Deep Contrasting Networks from Time Series Data: Application to Brain Network Analysis.

John Boaz Lee, Xiangnan Kong, Yihan Bao, Constance M. Moore

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Collective discovery of brain networks with unknown groups.

Xinyue Liu, Xiangnan Kong, Philip S. Yu

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Kernel-Based Feature Extraction for Collaborative Filtering.

Saket Sathe, Charu C. Aggarwal, Xiangnan Kong, Xinyue Liu

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

BiCycle: Item Recommendation with Life Cycles.

Xinyue Liu, Yuanfang Song, Charu C. Aggarwal, Yao Zhang, Xiangnan Kong

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Learning Node Embeddings in Interaction Graphs.

Yao Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016

Badge System Analysis and Design.

Jiawei Zhang, Xiangnan Kong, Philip S. Yu

CoRR, 2016

Bermuda: An Efficient MapReduce Triangle Listing Algorithm for Web-Scale Graphs.

Dongqing Xiao, Mohamed Y. Eltabakh, Xiangnan Kong

Proceedings of the 28th International Conference on Scientific and Statistical Database Management, 2016

Kernelized Matrix Factorization for Collaborative Filtering.

Xinyue Liu, Charu C. Aggarwal, Yu-Feng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

NetCycle: Collective Evolution Inference in Heterogeneous Information Networks.

Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Collective Traffic Prediction with Partially Observed Traffic History using Location-Based Social Media.

Xinyue Liu, Xiangnan Kong, Yanhua Li

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

Social badge system analysis.

Jiawei Zhang, Xiangnan Kong, Philip S. Yu

Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2016

2015

CelebrityNet: A Social Network Constructed from Large-Scale Online Celebrity Images.

Li-Jia Li, David A. Shamma, Xiangnan Kong, Sina Jafarpour, Roelof van Zwol, Xuanhui Wang

ACM Trans. Multim. Comput. Commun. Appl., 2015

Partial Network Alignment with Anchor Meta Path and Truncated Generic Stable Matching.

Jiawei Zhang, Weixiang Shao, Senzhang Wang, Xiangnan Kong, Philip S. Yu

CoRR, 2015

A review of heterogeneous data mining for brain disorders.

Bokai Cao, Xiangnan Kong, Philip S. Yu

CoRR, 2015

Identifying HIV-induced subgraph patterns in brain networks with side information.

Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu, Ann B. Ragin

Brain Informatics, 2015

A review of heterogeneous data mining for brain disorder identification.

Bokai Cao, Xiangnan Kong, Philip S. Yu

Brain Informatics, 2015

Python in Data Science Research and Education.

Randy C. Paffenroth, Xiangnan Kong

Proceedings of the 14th Python in Science Conference 2015 (SciPy 2015), Austin, Texas, July 6, 2015

PNA: Partial Network Alignment with Generic Stable Matching.

Jiawei Zhang, Weixiang Shao, Senzhang Wang, Xiangnan Kong, Philip S. Yu

Proceedings of the 2015 IEEE International Conference on Information Reuse and Integration, 2015

Mining Brain Networks Using Multiple Side Views for Neurological Disorder Identification.

Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu, Ann B. Ragin

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Identification of Discriminative Subgraph Patterns in fMRI Brain Networks in Bipolar Affective Disorder.

Bokai Cao, Liang Zhan, Xiangnan Kong, Philip S. Yu, Nathalie Vizueta, Lori L. Altshuler, Alex D. Leow

Proceedings of the Brain Informatics and Health - 8th International Conference, 2015

2014

HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks.

Chuan Shi, Xiangnan Kong, Yue Huang, Philip S. Yu, Bin Wu

IEEE Trans. Knowl. Data Eng., 2014

Multi-Label Classification Based on Multi-Objective Optimization.

Chuan Shi, Xiangnan Kong, Di Fu, Philip S. Yu, Bin Wu

ACM Trans. Intell. Syst. Technol., 2014

Privacy Preserving Social Network Publication Against Mutual Friend Attacks.

Chong-Jing Sun, Philip S. Yu, Xiangnan Kong, Yan Fu

Trans. Data Priv., 2014

Transferring heterogeneous links across location-based social networks.

Jiawei Zhang, Xiangnan Kong, Philip S. Yu

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Inferring the impacts of social media on crowdfunding.

Chun-Ta Lu, Sihong Xie, Xiangnan Kong, Philip S. Yu

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

When and Where: Predicting Human Movements Based on Social Spatial-Temporal Events.

Ning Yang, Xiangnan Kong, Fengjiao Wang, Philip S. Yu

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Large-Scale Multi-Label Learning with Incomplete Label Assignments.

Xiangnan Kong, Zhaoming Wu, Li-Jia Li, Ruofei Zhang, Philip S. Yu, Hang Wu, Wei Fan

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages.

Lifang He, Xiangnan Kong, Philip S. Yu, Xiaowei Yang, Ann B. Ragin, Zhifeng Hao

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Visual Recognition by Exploiting Latent Social Links in Image Collections.

Li-Jia Li, Xiangnan Kong, Philip S. Yu

Proceedings of the MultiMedia Modeling - 20th Anniversary International Conference, 2014

Discovering Organizational Correlations from Twitter.

Jingyuan Zhang, Xiaoxiao Shi, Xiangnan Kong, Hong-Han Shuai, Philip S. Yu

Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014

Low-Density Cut Based Tree Decomposition for Large-Scale SVM Problems.

Lifang He, Hong-Han Shuai, Xiangnan Kong, Zhifeng Hao, Xiaowei Yang, Philip S. Yu

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Collective Prediction of Multiple Types of Links in Heterogeneous Information Networks.

Bokai Cao, Xiangnan Kong, Philip S. Yu

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Tensor-Based Multi-view Feature Selection with Applications to Brain Diseases.

Bokai Cao, Lifang He, Xiangnan Kong, Philip S. Yu, Zhifeng Hao, Ann B. Ragin

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

NCR: A Scalable Network-Based Approach to Co-Ranking in Question-and-Answer Sites.

Jingyuan Zhang, Xiangnan Kong, Roger Jie Luo, Yi Chang, Philip S. Yu

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Active Learning: A Survey.

Charu C. Aggarwal, Xiangnan Kong, Quanquan Gu, Jiawei Han, Philip S. Yu

Proceedings of the Data Classification: Algorithms and Applications, 2014

2013

Transductive Multilabel Learning via Label Set Propagation.

Xiangnan Kong, Michael K. Ng, Zhi-Hua Zhou

IEEE Trans. Knowl. Data Eng., 2013

Brain network analysis: a data mining perspective.

Xiangnan Kong, Philip S. Yu

SIGKDD Explor., 2013

Meta Path-Based Collective Classification in Heterogeneous Information Networks

Xiangnan Kong, Bokai Cao, Philip S. Yu, Ying Ding, David J. Wild

CoRR, 2013

Discriminative Feature Selection for Uncertain Graph Classification.

Xiangnan Kong, Ann B. Ragin, Xue Wang, Philip S. Yu

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Multi-label classification by mining label and instance correlations from heterogeneous information networks.

Xiangnan Kong, Bokai Cao, Philip S. Yu

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Predicting Social Links for New Users across Aligned Heterogeneous Social Networks.

Jiawei Zhang, Xiangnan Kong, Philip S. Yu

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Multilabel Consensus Classification.

Sihong Xie, Xiangnan Kong, Jing Gao, Wei Fan, Philip S. Yu

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Predicting trends in social networks via dynamic activeness model.

Shuyang Lin, Xiangnan Kong, Philip S. Yu

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

Inferring anchor links across multiple heterogeneous social networks.

Xiangnan Kong, Jiawei Zhang, Philip S. Yu

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012

gMLC: a multi-label feature selection framework for graph classification.

Xiangnan Kong, Philip S. Yu

Knowl. Inf. Syst., 2012

Community detection in incomplete information networks.

Wangqun Lin, Xiangnan Kong, Philip S. Yu, Quanyuan Wu, Yan Jia, Chuan Li

Proceedings of the 21st World Wide Web Conference 2012, 2012

Multi-Objective Multi-Label Classification.

Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Transfer Significant Subgraphs across Graph Databases.

Xiaoxiao Shi, Xiangnan Kong, Philip S. Yu

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

HeteRecom: a semantic-based recommendation systemin heterogeneous networks.

Chuan Shi, Chong Zhou, Xiangnan Kong, Philip S. Yu, Gang Liu, Bai Wang

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Relevance search in heterogeneous networks.

Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie, Bin Wu

Proceedings of the 15th International Conference on Extending Database Technology, 2012

Meta path-based collective classification in heterogeneous information networks.

Xiangnan Kong, Philip S. Yu, Ying Ding, David J. Wild

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Monitoring knowledge flow through scholarly networks.

Erjia Yan, Ying Ding, Xiangnan Kong

Proceedings of the Information, Interaction, Innovation: Celebrating the Past, Constructing the Present and Creating the Future, 2012

2011

Multi-Label Collective Classification.

Xiangnan Kong, Xiaoxiao Shi, Philip S. Yu

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Multi-label Ensemble Learning.

Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Dual active feature and sample selection for graph classification.

Xiangnan Kong, Wei Fan, Philip S. Yu

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Positive and Unlabeled Learning for Graph Classification.

Yuchen Zhao, Xiangnan Kong, Philip S. Yu

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

An ensemble-based approach to fast classification of multi-label data streams.

Xiangnan Kong, Philip S. Yu

Proceedings of the 7th International Conference on Collaborative Computing: Networking, 2011

2010

Semi-supervised feature selection for graph classification.

Xiangnan Kong, Philip S. Yu

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Multi-label Feature Selection for Graph Classification.

Xiangnan Kong, Philip S. Yu

Proceedings of the ICDM 2010, 2010