2023

• [AAAI]

  Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer Jidapa Thadajarassiri, Thomas Hartvigsen, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner AAAI Conference on Artificial Intelligence (AAAI)

2022

• [KDD]

  ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data Yao Su, Zhentian Qian, Xiangnan Kong, Lifang He ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [CIKM]

  Stop&Hop: Early Classification of Irregular Time Series Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner ACM International Conference on Information and Knowledge Management (CIKM)

• [ICDM]

  ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration Yao Su, Xin Dai, Lifang He, Xiangnan Kong IEEE International Conference on Data Mining (ICDM)

• [ICDM]

  STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo IEEE International Conference on Data Mining (ICDM)

2021

• [KDD]

  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 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [AAAI]

  Semi-Supervised Knowledge Amalgamation for Sequence Classification Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner AAAI Conference on Artificial Intelligence (AAAI)

• [SDM]

  CiNet: Redesigning Deep Neural Networks for Efficient Mobile-Cloud Collaborative Inference Xin Dai, Xiangnan Kong, Tian Guo, Yixian Huang SIAM International Conference on Data Mining (SDM)

• [CIKM]

  FiShNet: Fine-Grained Filter Sharing for Resource-Efficient Multi-Task Learning Xin Dai, Xiangnan Kong, Tian Guo, Xinlu He ACM International Conference on Information and Knowledge Management (CIKM)

• [ICDM]

  Self-learn to Explain Siamese Networks Robustly Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie IEEE International Conference on Data Mining (ICDM)

• [BIGDATA]

  Human-like Explanation for Text Classification With Limited Attention Supervision Dongyu Zhang, Cansu Sen, Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner IEEE International Conference on Big Data (BIGDATA)

• [ICPE]

  PieSlicer: Characterizing and Dynamically Cutting Cloud Inference Response Time Samuel Ogden, Xiangnan Kong, Srinivas Rangarajan ACM/SPEC International Conference on Performance Engineering (ICPE)

• [WWWJ]

  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: Internet and Web Information Systems (WWWJ)

2020

• [TKDE]

  Role-based Graph Embeddings Nesreen K. Ahmed, Ryan Rossi, John Boaz Lee, Theodore L. Willke, Rong Zhou, Xiangnan Kong, Hoda Eldardiry IEEE Transactions on Knowledge and Data Engineering (TKDE)

• [KDD]

  Recurrent Networks for Guided Multi-Attention Classification Xin Dai, Xiangnan Kong, Tian Guo, John Boaz Lee, Xinyue Liu, Constance M. Moore ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [KDD]

  Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [KDD]

  Recurrent Halting Chain for Early Multi-label Classification Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [ACL]

  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 Conference of the Association for Computational Linguistics (ACL)

• [CIKM]

  EPNet: Learning to Exit with Flexible Multi-Branch Network Xin Dai, Xiangnan Kong, Tian Guo ACM International Conference on Information and Knowledge Management (CIKM)

• [CIKM]

  Learning to Selectively Update State Neurons in Recurrent Networks Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner ACM International Conference on Information and Knowledge Management (CIKM)

• [SDM]

  Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions John Boaz Lee, Xiangnan Kong, Constance M. Moore, Nesreen K. Ahmed SIAM International Conference on Data Mining (SDM)

• [SDM]

  Dual-Attention Recurrent Networks for Affine Registration of Neuroimaging Data Xin Dai, Xiangnan Kong, Xinyue Liu, John Boaz Lee, Constance M. Moore SIAM International Conference on Data Mining (SDM)

• [TBD]

  Off-Deployment Traffic Estimation --- A Traffic Generative Adversarial Networks Approach Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo IEEE Transactions on Big Data (TBD)

• [BIGDATA]

  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 IEEE International Conference on Big Data (BIGDATA)

• [BIGDATA]

  Learning Similarity-Preserving Meta-Embedding for Text Mining Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner IEEE International Conference on Big Data (BIGDATA)

• [BIGDATA]

  MLAS: Metric Learning on Attributed Sequences Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora IEEE International Conference on Big Data (BIGDATA)

• [BIGDATA]

  Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks Hang Yin, Xinyue Liu, Xiangnan Kong IEEE International Conference on Big Data (BIGDATA)

• [IPM]

  Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin Information Processing and Management (IPM)

• [DASFAA]

  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 Database Systems for Advanced Applications (DASFAA)

• [APWeb]

  Multi-task Attributed Graphical Lasso Yao Zhang, Yun Xiong, Xiangnan Kong, Xinyue Liu, Yangyong Zhu APWeb-WAIM International Joint Conference on Web and Big Data (APWeb)

• [FEMNLP]

  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 Findings of EMNLP (FEMNLP)

2019

• [TKDE]

  GraphInception: Convolutional Neural Networks for Collective Classification in Heterogeneous Information Networks Yun Xiong, Yizhou Zhang, Xiangnan Kong, Huidi Chen, Yangyong Zhu IEEE Transactions on Knowledge and Data Engineering (TKDE)

• [TKDE]

  IGE+: A Framework for Learning Node Embeddings in Interaction Graphs Yao Zhang, Yun Xiong, Xiangnan Kong, Zhuang Niu, Yangyong Zhu IEEE Transactions on Knowledge and Data Engineering (TKDE)

• [KDD]

  Adaptive-Halting Policy Network for Early Classification Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [WWW]

  Signed Distance-based Deep Memory Recommender Thanh Tran, Xinyue Liu, Kyumin Lee, Xiangnan Kong International World Wide Web Conferences (WWW)

• [ICDM]

  TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo IEEE International Conference on Data Mining (ICDM)

• [SDM]

  AMAS: Attention Model for Attributed Sequence Classification Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner SIAM International Conference on Data Mining (SDM)

• [CIKM]

  Graph Convolutional Networks with Motif-based Attention John Boaz Lee, Ryan Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao ACM International Conference on Information and Knowledge Management (CIKM)

• [CIKM]

  Author Set Identification via Quasi-Clique Discovery Yuyan Zheng, Chuan Shi, Xiangnan Kong, Yanfang Ye ACM International Conference on Information and Knowledge Management (CIKM)

• [ASONAM]

  Competitive Opinion Maximization in Social Networks Jianjun Luo, Xinyue Liu, Xiangnan Kong IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

• [BIGDATA]

  Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner IEEE International Conference on Big Data (BIGDATA)

• [BIGDATA]

  Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora IEEE International Conference on Big Data (BIGDATA)

• [DASFAA]

  Net2Text: An Edge Labelling Language Model for Personalized Comment Generation Shaofeng Xu, Yun Xiong, Xiangnan Kong, Yangyong Zhu Database Systems for Advanced Applications (DASFAA)

• [BHI]

  Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner IEEE International Conference on Biomedical and Health Informatics (BHI)

• [APNS]

  Learning Compact Graph Representations via an Encoder-Decoder Network John Boaz Lee, Xiangnan Kong Applied Network Science (APNS)

• [TCN]

  Locally Weighted Fusion of Structural and Attribute Information in Graph Clustering Yafang Li, Caiyan Jia, Xiangnan Kong, Liu Yang, Jian Yu IEEE Transactions on Cybernetics (TCN)

2018

• [KDD]

  Graph Classification using Structural Attention John Boaz Lee, Ryan Rossi, Xiangnan Kong ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [KDD]

  Active Opinion Maximization in Social Networks Xinyue Liu, Xiangnan Kong, Philip S. Yu ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [WWW]

  Deep Collective Classification in Heterogeneous Information Networks Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu International World Wide Web Conferences (WWW)

• [TKDE]

  NetCycle+: A Framework for Collective Evolution Inference in Dynamic Heterogeneous Networks Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu IEEE Transactions on Knowledge and Data Engineering (TKDE)

• [ICDE]

  Sharing Uncertain Graphs Using Syntactic Private Graph Models Dongqing Xiao, Xiangnan Kong, Mohamed Y. Eltabakh IEEE International Conference on Data Engineering (ICDE)

• [ICDM]

  Coherent Graphical Lasso for Brain Network Discovery Hang Yin, Xinyue Liu, Xiangnan Kong IEEE International Conference on Data Mining (ICDM)

• [ICDM]

  TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks Xinyue Liu, Xiangnan Kong, Lei Liu, Kuorong Chiang IEEE International Conference on Data Mining (ICDM)

• [BIGDATA]

  One-Shot Learning on Attributed Sequences Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Aditya Arora, Jihane Zouaoui IEEE International Conference on Big Data (BIGDATA)

• [BIBM]

  Predicting Disease-related Associations by Heterogeneous Network Embedding Yun Xiong, Lu Ruan, Mengjie Guo, Xiangnan Kong, Yangyong Zhu, Wei Wang International Conference on Bioinformatics and Biomedicine (BIBM)

• [ACML]

  Clustering Uncertain Graphs with Node Attributes Yafang Li, Xiangnan Kong, Caiyan Jia, Jianqiang Li Asian Conference on Machine Learning (ACML)

• [DASFAA]

  Tracking Dynamic Magnet Communities: Insights from a Network Perspective Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu Database Systems for Advanced Applications (DASFAA)

• [DASFAA]

  Functional-Oriented Relationship Strength Estimation: From Online Events to Offline Interactions Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu, Jianqiang Li, Shimin Zhao Database Systems for Advanced Applications (DASFAA)

• [HEALTHINF]

  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, Shimin Zhao, Suranjan De International Conference on Health Informatics (HEALTHINF)

• [HEALTHINF]

  Early Prediction of MRSA Infections Using Electronic Health Records Thomas Hartvigsen, Cansu Sen, Sarah Brownell, Erin Teeple, Xiangnan Kong, Elke A. Rundensteiner International Conference on Health Informatics (HEALTHINF)

• [MADW]

  Bidirectional LSTM-CRF for adverse drug event tagging in electronic health records Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Elke A. Rundensteiner, Xiangnan Kong International Workshop on Medication and Adverse Drug Event Detection (MADW)

2017

• [ICDM]

  BiCycle: Item Recommendation with Life Cycles Xinyue Liu, Yuanfang Song, Charu C. Aggarwal, Yao Zhang, Xiangnan Kong IEEE International Conference on Data Mining (ICDM)

• [ICDM]

  Kernel-Based Feature Extraction For Collaborative Filtering Saket Sathe, Charu C. Aggarwal, Xiangnan Kong, Xinyue Liu IEEE International Conference on Data Mining (ICDM)

• [CIKM]

  Learning Node Embeddings in Interaction Graphs Yao Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu ACM International Conference on Information and Knowledge Management (CIKM)

• [SDM]

  Identifying Deep Contrasting Networks from Time Series Data: Application to Brain Network Analysis John Boaz Lee, Xiangnan Kong, Yihan Bao, Constance M. Moore SIAM International Conference on Data Mining (SDM)

• [SDM]

  Meta-Path Graphical Lasso for Learning Heterogeneous Connectivities Yao Zhang, Yun Xiong, Xinyue Liu, Xiangnan Kong, Yangyong Zhu SIAM International Conference on Data Mining (SDM)

• [SDM]

  Unified and Contrasting Graphical Lasso for Brain Network Discovery Xinyue Liu, Xiangnan Kong, Ann B. Ragin SIAM International Conference on Data Mining (SDM)

• [IJCNN]

  Collective Discovery of Brain Networks with Unknown Groups Xinyue Liu, Xiangnan Kong, Philip S. Yu International Joint Conference on Neural Networks (IJCNN)

• [ICSC]

  Using Social Sensing to Discover Trends in Public Emotion Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu IEEE International Conference on Semantic Computing (ICSC)

• [SIGWEB]

  Discover trends in public emotion using social sensing Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu SIGWEB Newsletter (SIGWEB)

2016

• [KDD]

  NetCycle: Collective Evolution Inference in Heterogeneous Information Networks Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [SDM]

  Kernelized Matrix Factorization for Collaborative Filtering Xinyue Liu, Charu C. Aggarwal, Yu-Feng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe SIAM International Conference on Data Mining (SDM)

• [CIKM]

  Collective Traffic Prediction with Partially Observed Traffic History using Location-Base Social Media Xinyue Liu, Xiangnan Kong, Yanhua Li ACM International Conference on Information and Knowledge Management (CIKM)

• [SSDBM]

  Bermuda: An Efficient MapReduce Triangle Listing Algorithm for Web-Scale Graphs Dongqing Xiao, Mohamed Y. Eltabakh, Xiangnan Kong International Conference on Scientific and Statistical Database Management (SSDBM)

• [ASONAM]

  Social Badge System Analysis Jiawei Zhang, Xiangnan Kong, Philip S. Yu IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

2015

• [ICDM]

  Mining Brain Networks using Multiple Side Views for Neurological Disorder Identification Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu, Ann B. Ragin IEEE International Conference on Data Mining (ICDM)

• [BIN]

  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 (BIN)

• [BIN]

  A review of heterogeneous data mining for brain disorder Identification for Brain Informatics Bokai Cao, Xiangnan Kong, Philip S. Yu Brain Informatics (BIN)

• [IRI]

  PNA: Partial Network Alignment with Generic Stable Matching Jiawei Zhang, Weixiang Shao, Senzhang Wang, Xiangnan Kong, Philip S. Yu IEEE International Conference on Information Reuse and Integration (IRI)

• [NeuImg]

  Determinants of HIV-induced brain changes in three different periods of the early clinical course: A Data Mining Analysis Bokai Cao, Xiangnan Kong, Casey Kettering, Philip S. Yu, Ann B. Ragin NeuroImage: Clinical (NeuImg)

• [BIH]

  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 Brain Informatics and Health (BIH)

• [TOMM]

  CelebrityNet: A Social Network Constructed from Large Scale Online Celebrity Images Li-Jia Li, David Shamma, Xiangnan Kong, Sina Jafarpour, Roelof van Zwol, Xuanhui Wang ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)

2014

• [TKDE]

  HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks Chuan Shi, Xiangnan Kong, Yue Huang, Philip S. Yu, Bin Wu IEEE Transactions on Knowledge and Data Engineering (TKDE)

• [ICDM]

  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 IEEE International Conference on Data Mining (ICDM)

• [ICDM]

  Collective Prediction of Multiple Types of Links in Heterogeneous Information Networks Bokai Cao, Xiangnan Kong, Philip S. Yu IEEE International Conference on Data Mining (ICDM)

• [ICDM]

  Low-Density Cut based Tree Decomposition for Large-Scale SVM Problems Lifang He, Honghan Shuai, Xiangnan Kong, Xiaowei Yang, Philip S. Yu IEEE International Conference on Data Mining (ICDM)

• [SDM]

  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 SIAM International Conference on Data Mining (SDM)

• [SDM]

  When and Where: Predicting Human Movements Based on Social Spatial-Temporal Events Ning Yang, Xiangnan Kong, Fengjiao Wang, Philip S. Yu SIAM International Conference on Data Mining (SDM)

• [SDM]

  DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages Lifang He, Xiangnan Kong, Philip S. Yu, Ann B. Ragin, Zhifeng Hao, Xiaowei Yang SIAM International Conference on Data Mining (SDM)

• [WSDM]

  Transferring Heterogeneous Links across Location-Based Social Networks Jiawei Zhang, Xiangnan Kong, Philip S. Yu ACM International Conference on Web Search and Data Mining (WSDM)

• [WSDM]

  Inferring the Impacts of Social Media on Crowdfunding Chun-Ta Lu, Sihong Xie, Xiangnan Kong, Philip S. Yu ACM International Conference on Web Search and Data Mining (WSDM)

• [CIKM]

  NCR: A Scalable Network-Based Approach to Co-Ranking in Question-and-Answer Sites Jingyuan Zhang, Xiangnan Kong, Jie Luo, Yi Chang, Philip S. Yu ACM International Conference on Information and Knowledge Management (CIKM)

• [BOOK]

  Active Learning: A Survey Charu C. Aggarwal, Xiangnan Kong, Quanquan Gu, Jiawei Han, Philip S. Yu Data Classification: Algorithms and Applications (BOOK)

• [KDDexp]

  Brain Network Analysis: A Data Mining Perspective Xiangnan Kong, Philip S. Yu ACM SIGKDD Explorations (KDDexp)

• [TDP]

  Privacy Preserving Social Network Publication Against Mutual Friend Attacks Chongjing Sun, Philip S. Yu, Xiangnan Kong, Yan Fu Transactions on Data Privacy (TDP)

• [ESNAM]

  Graph Classification in Heterogeneous Networks Xiangnan Kong, Philip S. Yu Encyclopedia of Social Networks and Mining (ESNAM)

• [ICDMW]

  Discovering organizational correlations from twitter Jingyuan Zhang, Xiaoxiao Shi, Xiangnan Kong, Honghan Shuai, Philip S. Yu IEEE International Conference on Data Mining Workshops (ICDMW)

2013

• [KDD]

  Multi-label Classification by Mining Instance and Label Correlation from Heterogeneous Information Network Xiangnan Kong, Bokai Cao, Philip S. Yu ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [TKDE]

  Transductive Multi-Label Learning via Label Set Propagation Xiangnan Kong, Michael Ng, Zhi-Hua Zhou IEEE Transactions on Knowledge and Data Engineering (TKDE)

• [TIST]

  Multi-label classification based on Multi-Objective Optimization Chuan Shi, Xiangnan Kong, Di Fu, Philip S. Yu, Bai Wang ACM Transactions on Intelligent Systems and Technology (TIST)

• [ICDM]

  Multilabel Consensus Classification Sihong Xie, Xiangnan Kong, Jing Gao, Wei Fan, Philip S. Yu IEEE International Conference on Data Mining (ICDM)

• [ICDM]

  Predicting Social Links for New Users across Aligned Heterogeneous Social Networks Jiawei Zhang, Xiangnan Kong, Philip S. Yu IEEE International Conference on Data Mining (ICDM)

• [CIKM]

  Inferring Anchor Links across Heterogeneous Social Networks Xiangnan Kong, Jiawei Zhang, Philip S. Yu ACM International Conference on Information and Knowledge Management (CIKM)

• [CIKM]

  Predicting Trends in Social Networks via Dynamic Activeness Model Shuyang Lin, Xiangnan Kong, Philip S. Yu ACM International Conference on Information and Knowledge Management (CIKM)

• [SDM]

  Discriminative Feature Selection for Uncertain Graph Classification Xiangnan Kong, Philip S. Yu, Xue Wang, Ann B. Ragin SIAM International Conference on Data Mining (SDM)

• [MMM]

  Visual Recognition by Exploiting Latent Social Links in Image Collections Li-Jia Li, Xiangnan Kong, Philip S. Yu International Conference on MultiMedia Modeling (MMM)

• [ICDMW]

  Privacy preserving social network publication against mutual friend attacks Chongjing Sun, Philip S. Yu, Xiangnan Kong, Yan Fu IEEE International Conference on Data Mining Workshops (ICDMW)

2012

• [WWW]

  Community Detection in Incomplete Information Networks Guanqun Wang, Xiangnan Kong, Philip S. Yu, Quanyuan Wu, Yan Jia, Chuan Li International World Wide Web Conferences (WWW)

• [SDM]

  Multi-Objective Multi-Label Classification Chuan Shi, Xiangnan Kong, Philip S. Yu SIAM International Conference on Data Mining (SDM)

• [SDM]

  Transfer Significant Subgraphs across Graph Databases Xiaoxiao Shi, Xiangnan Kong, Philip S. Yu SIAM International Conference on Data Mining (SDM)

• [CIKM]

  Meta Path-Based Collective Classification in Heterogeneous Information Networks Xiangnan Kong, Philip S. Yu, Ying Ding, David Wild ACM International Conference on Information and Knowledge Management (CIKM)

• [EDBT]

  Relevance Search in Heterogeneous Networks Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie, Bin Wu International Conference on Extending Database Technology (EDBT)

• [ASIST]

  Monitoring knowledge flow through scholarly networks Erjia Yan, Ying Ding, Xiangnan Kong American Society for Information Science and Technology (ASIST)

• [KDDdemo]

  HeteRecom: A Semantic Recommendation System in Heterogeneous Networks Chuan Shi, Chong Zhou, Xiangnan Kong, Philip S. Yu Demo Session in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDDdemo)

2011

• [KDD]

  Dual Active Feature and Sample Selection for Graph Classification Xiangnan Kong, Wei Fan, Philip S. Yu ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [SDM]

  Multi-Label Collective Classification Xiangnan Kong, Xiaoxiao Shi, Philip S. Yu SIAM International Conference on Data Mining (SDM)

• [KAIS]

  gMLC: a Multi-label Feature Selection Framework for Graph Classification Xiangnan Kong, Philip S. Yu Knowledge and Information Systems (KAIS)

• [ICDM]

  Positive and Unlabeled Learning for Graph Classification Yuchen Zhao, Xiangnan Kong, Philip S. Yu IEEE International Conference on Data Mining (ICDM)

• [ECML]

  Multi-label Ensemble Learning Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML)

• [ColCom]

  An Ensemble-based Approach to Fast Classification of Multi-label Data Streams Xiangnan Kong, Philip S. Yu IEEE International Conference on Collaborative Computing: Networking, Application and Worksharing (ColCom)

2010

• [KDD]

  Semi-supervised Feature Selection for Graph Classification Xiangnan Kong, Philip S. Yu ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

• [ICDM]

  Multi-Label Feature Selection for Graph Classification Xiangnan Kong, Philip S. Yu IEEE International Conference on Data Mining (ICDM)

• [JCRD]

  A Transductive Multi-Label Classification Method for Weak Labeling Xiangnan Kong, Ming Li, Yuan Jiang, Zhi-Hua Zhou Journal of Computer Research and Development (JCRD)