Xiangnan Kong - RankMe

167 papers A* 38A 29B 9C 2Misc 2Journal 54Unranked 31

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	End-to-End Deep Learning for Structural Brain Imaging: A Unified Framework. AAAI Spring Symposia Yao Su, Keqi Han, Mingjie Zeng, Lichao Sun, Liang Zhan, Carl Yang, Lifang He, Xiangnan Kong
2025	J	`jnl`	End-to-End Deep Learning for Structural Brain Imaging: A Unified Framework. CoRR Yao Su, Keqi Han, Mingjie Zeng, Lichao Sun, Liang Zhan, Carl Yang, Lifang He, Xiangnan Kong
2024	A*	`conf`	Amalgamating Multi-Task Models with Heterogeneous Architectures. AAAI Jidapa Thadajarassiri, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner
2024	B	`conf`	SkipSNN: Efficiently Classifying Spike Trains with Event-attention. IEEE Big Data Hang Yin, Yao Su, Liping Liu, Thomas Hartvigsen, Xin Dai, Xiangnan Kong
2024	J	`jnl`	SkipSNN: Efficiently Classifying Spike Trains with Event-attention. CoRR Hang Yin, Yao Su, Liping Liu, Thomas Hartvigsen, Xin Dai, Xiangnan Kong
2023	J	`jnl`	Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks. CoRR Thomas Hartvigsen, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner
2023	A*	`conf`	Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer. AAAI Jidapa Thadajarassiri, Thomas Hartvigsen, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner
2023	B	`conf`	Multi-Item Continuous Influence Maximization. IEEE Big Data Jianjun Luo, Ryan A. Rossi, Xiangnan Kong, Yanhua Li
2023	B	`conf`	Multi-State Brain Network Discovery. IEEE Big Data Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong
2023	J	`jnl`	Multi-State Brain Network Discovery. CoRR Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong
2023	A*	`conf`	One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. KDD Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong
2023	J	`jnl`	One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. CoRR Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong
2022	A*	`conf`	ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. ICDM Yao Su, Xin Dai, Lifang He, Xiangnan Kong
2022	J	`jnl`	ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. CoRR Yao Su, Xin Dai, Lifang He, Xiangnan Kong
2022	A*	`conf`	ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. KDD Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong
2022	J	`jnl`	ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. CoRR Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong
2022	J	`jnl`	Multi-task attributed graphical lasso and its application in fund classification. World Wide Web Yao Zhang, Sijia Peng, Yun Xiong, Xiangnan Kong, Xinyue Liu, Yangyong Zhu
2022	J	`jnl`	Off-Deployment Traffic Estimation - A Traffic Generative Adversarial Networks Approach. IEEE Trans. Big Data Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
2022	J	`jnl`	One-Shot Learning on Attributed Sequences. CoRR Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Aditya Arora, Jihane Zouaoui
2022	J	`jnl`	Role-Based Graph Embeddings. IEEE Trans. Knowl. Data Eng. Nesreen K. Ahmed, Ryan A. Rossi, John Boaz Lee, Theodore L. Willke, Rong Zhou, Xiangnan Kong, Hoda Eldardiry
2022	A*	`conf`	STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation. ICDM Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
2022	A	`conf`	Stop&Hop: Early Classification of Irregular Time Series. CIKM Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner
2022	J	`jnl`	Stop&Hop: Early Classification of Irregular Time Series. CoRR Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner
2021	A	`conf`	CiNet: Redesigning Deep Neural Networks for Efficient Mobile-Cloud Collaborative Inference. SDM Xin Dai, Xiangnan Kong, Tian Guo, Yixian Huang
2021	A*	`conf`	Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks. KDD Hang Yin, John Boaz Lee, Xiangnan Kong, Thomas Hartvigsen, Sihong Xie
2021	A	`conf`	FiShNet: Fine-Grained Filter Sharing for Resource-Efficient Multi-Task Learning. CIKM Xin Dai, Xiangnan Kong, Tian Guo, Xinlu He
2021	J	`jnl`	Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks. CoRR Hang Yin, Xinyue Liu, Xiangnan Kong
2021	J	`jnl`	GraphInception: Convolutional Neural Networks for Collective Classification in Heterogeneous Information Networks. IEEE Trans. Knowl. Data Eng. Yun Xiong, Yizhou Zhang, Xiangnan Kong, Huidi Chen, Yangyong Zhu
2021	—	`conf`	Human-like Explanation for Text Classification With Limited Attention Supervision. IEEE BigData Dongyu Zhang, Cansu Sen, Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
2021	J	`jnl`	IGE+: A Framework for Learning Node Embeddings in Interaction Graphs. IEEE Trans. Knowl. Data Eng. Yao Zhang, Yun Xiong, Xiangnan Kong, Zhuang Niu, Yangyong Zhu
2021	B	`conf`	PieSlicer: Dynamically Improving Response Time for Cloud-based CNN Inference. ICPE Samuel S. Ogden, Xiangnan Kong, Tian Guo
2021	A*	`conf`	Self-learn to Explain Siamese Networks Robustly. ICDM Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie
2021	J	`jnl`	Self-learn to Explain Siamese Networks Robustly. CoRR Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie
2021	A*	`conf`	Semi-Supervised Knowledge Amalgamation for Sequence Classification. AAAI Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
2020	—	`conf`	A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events. EMNLP (Findings) Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke A. Rundensteiner
2020	—	`conf`	Code2Text: Dual Attention Syntax Annotation Networks for Structure-Aware Code Translation. DASFAA (3) Yun Xiong, Shaofeng Xu, Keyao Rong, Xinyue Liu, Xiangnan Kong, Shanshan Li, Philip S. Yu, Yangyong Zhu
2020	A*	`conf`	Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. KDD Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
2020	A	`conf`	Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions. SDM John Boaz Lee, Xiangnan Kong, Constance M. Moore, Nesreen K. Ahmed
2020	A	`conf`	Dual-Attention Recurrent Networks for Affine Registration of Neuroimaging Data. SDM Xin Dai, Xiangnan Kong, Xinyue Liu, John Boaz Lee, Constance M. Moore
2020	A	`conf`	EPNet: Learning to Exit with Flexible Multi-Branch Network. CIKM Xin Dai, Xiangnan Kong, Tian Guo
2020	—	`conf`	Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks. IEEE BigData Hang Yin, Xinyue Liu, Xiangnan Kong
2020	A*	`conf`	Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words? ACL Cansu Sen, Thomas Hartvigsen, Biao Yin, Xiangnan Kong, Elke A. Rundensteiner
2020	—	`conf`	Learning Similarity-Preserving Meta-Embedding for Text Mining. IEEE BigData Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
2020	A	`conf`	Learning to Selectively Update State Neurons in Recurrent Networks. CIKM Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner
2020	—	`conf`	MLAS: Metric Learning on Attributed Sequences. IEEE BigData Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
2020	J	`jnl`	MLAS: Metric Learning on Attributed Sequences. CoRR Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
2020	—	`conf`	Multi-task Attributed Graphical Lasso. APWeb/WAIM (1) Yao Zhang, Yun Xiong, Xiangnan Kong, Xinyue Liu, Yangyong Zhu
2020	A*	`conf`	Recurrent Halting Chain for Early Multi-label Classification. KDD Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner
2020	A*	`conf`	Recurrent Networks for Guided Multi-Attention Classification. KDD Xin Dai, Xiangnan Kong, Tian Guo, John Boaz Lee, Xinyue Liu, Constance M. Moore
2020	J	`jnl`	Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks. Inf. Process. Manag. Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin
2020	—	`conf`	Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding. IEEE BigData Xiao Qin, Cao Xiao, Tengfei Ma, Tabassum Kakar, Susmitha Wunnava, Xiangnan Kong, Elke A. Rundensteiner, Fei Wang
2019	A	`conf`	AMAS: Attention Model for Attributed Sequence Classification. SDM Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner
2019	A*	`conf`	Adaptive-Halting Policy Network for Early Classification. KDD Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner
2019	—	`conf`	Attributed Sequence Embedding. IEEE BigData Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
2019	J	`jnl`	Attributed Sequence Embedding. CoRR Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
2019	A	`conf`	Author Set Identification via Quasi-Clique Discovery. CIKM Yuyan Zheng, Chuan Shi, Xiangnan Kong, Yanfang Ye
2019	—	`conf`	Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining. BHI Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
2019	B	`conf`	Competitive opinion maximization in social networks. ASONAM Jianjun Luo, Xinyue Liu, Xiangnan Kong
2019	A	`conf`	Graph Convolutional Networks with Motif-based Attention. CIKM John Boaz Lee, Ryan A. Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao
2019	—	`conf`	Learning Temporal Relevance in Longitudinal Medical Notes. IEEE BigData Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
2019	J	`jnl`	Learning compact graph representations via an encoder-decoder network. Appl. Netw. Sci. John Boaz Lee, Xiangnan Kong
2019	J	`jnl`	Locally Weighted Fusion of Structural and Attribute Information in Graph Clustering. IEEE Trans. Cybern. Yafang Li, Caiyan Jia, Xiangnan Kong, Liu Yang, Jian Yu
2019	—	`conf`	Net2Text: An Edge Labelling Language Model for Personalized Review Generation. DASFAA (1) Shaofeng Xu, Yun Xiong, Xiangnan Kong, Yangyong Zhu
2019	—	`conf`	NetMerger: Predicting Cross-network Links in Merged Heterogeneous Networks. WI (Companion) Yao Zhang, Yun Xiong, Lu Ruan, Xiangnan Kong, Yangyong Zhu
2019	—	`conf`	Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention. IEEE BigData Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
2019	A*	`conf`	Signed Distance-based Deep Memory Recommender. WWW Thanh Tran, Xinyue Liu, Kyumin Lee, Xiangnan Kong
2019	J	`jnl`	Signed Distance-based Deep Memory Recommender. CoRR Thanh Tran, Xinyue Liu, Kyumin Lee, Xiangnan Kong
2019	A*	`conf`	TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks. ICDM Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
2018	A*	`conf`	Active Opinion Maximization in Social Networks. KDD Xinyue Liu, Xiangnan Kong, Philip S. Yu
2018	—	`conf`	Bidirectional LSTM-CRF for Adverse Drug Event Tagging in Electronic Health Records. Medication and Adverse Drug Event Detection Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Elke A. Rundensteiner, Xiangnan Kong
2018	C	`conf`	Clustering Uncertain Graphs with Node Attributes. ACML Yafang Li, Xiangnan Kong, Caiyan Jia, Jianqiang Li
2018	A*	`conf`	Coherent Graphical Lasso for Brain Network Discovery. ICDM Hang Yin, Xiangnan Kong, Xinyue Liu
2018	A*	`conf`	Deep Collective Classification in Heterogeneous Information Networks. WWW Yizhou Zhang, Yun Xiong, Xiangnan Kong, Shanshan Li, Jinhong Mi, Yangyong Zhu
2018	Misc	`conf`	Deep Learning Strategies for Automatic Detection of Medication and Adverse Drug Events from Electronic Health Records. AMIA Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Elke A. Rundensteiner, Xiangnan Kong
2018	—	`conf`	Early Prediction of MRSA Infections using Electronic Health Records. HEALTHINF Thomas Hartvigsen, Cansu Sen, Sarah Brownell, Erin Teeple, Xiangnan Kong, Elke A. Rundensteiner
2018	—	`conf`	Functional-Oriented Relationship Strength Estimation: From Online Events to Offline Interactions. DASFAA (1) Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu, Shimin Zhao, Shanshan Li
2018	—	`ch.`	Graph Classification in Heterogeneous Networks. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. Xiangnan Kong, Philip S. Yu
2018	A*	`conf`	Graph Classification using Structural Attention. KDD John Boaz Lee, Ryan A. Rossi, Xiangnan Kong
2018	J	`jnl`	Higher-order Graph Convolutional Networks. CoRR John Boaz Lee, Ryan A. Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao
2018	J	`jnl`	Learning Role-based Graph Embeddings. CoRR Nesreen K. Ahmed, Ryan A. Rossi, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Rong Zhou, Hoda Eldardiry
2018	—	`conf`	Multi-layered Learning for Information Extraction from Adverse Drug Event Narratives. BIOSTEC (Selected Papers) Susmitha Wunnava, Xiao Qin, Tabassum Kakar, M. L. Tlachac, Xiangnan Kong, Elke A. Rundensteiner, Sanjay K. Sahoo, Suranjan De
2018	J	`jnl`	NetCycle+: A Framework for Collective Evolution Inference in Dynamic Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. Yun Xiong, Yizhou Zhang, Xiangnan Kong, Yangyong Zhu
2018	—	`conf`	One Size Does Not Fit All: An Ensemble Approach Towards Information Extraction from Adverse Drug Event Narratives. HEALTHINF Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke A. Rundensteiner, Sanjay K. Sahoo, Suranjan De
2018	—	`conf`	One-Shot Learning on Attributed Sequences. IEEE BigData Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Aditya Arora, Jihane Zouaoui
2018	—	`conf`	Predicting Disease-related Associations by Heterogeneous Network Embedding. BIBM Yun Xiong, Lu Ruan, Mengjie Guo, Chunlei Tang, Xiangnan Kong, Yangyong Zhu, Wei Wang
2018	A*	`conf`	Sharing Uncertain Graphs Using Syntactic Private Graph Models. ICDE Dongqing Xiao, Mohamed Y. Eltabakh, Xiangnan Kong
2018	—	`conf`	Tracking Dynamic Magnet Communities: Insights from a Network Perspective. DASFAA (1) Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu
2018	A*	`conf`	TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks. ICDM Xinyue Liu, Xiangnan Kong, Lei Liu, Kuorong Chiang
2018	J	`jnl`	TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks. CoRR Xinyue Liu, Xiangnan Kong, Lei Liu, Kuorong Chiang
2017	J	`jnl`	A Framework for Generalizing Graph-based Representation Learning Methods. CoRR Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Hoda Eldardiry
2017	A*	`conf`	BiCycle: Item Recommendation with Life Cycles. ICDM Xinyue Liu, Yuanfang Song, Charu C. Aggarwal, Yao Zhang, Xiangnan Kong
2017	B	`conf`	Collective discovery of brain networks with unknown groups. IJCNN Xinyue Liu, Xiangnan Kong, Philip S. Yu
2017	J	`jnl`	Deep Graph Attention Model. CoRR John Boaz Lee, Ryan A. Rossi, Xiangnan Kong
2017	J	`jnl`	Discover trends in public emotion using social sensing. SIGWEB Newsl. Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu
2017	A	`conf`	Identifying Deep Contrasting Networks from Time Series Data: Application to Brain Network Analysis. SDM John Boaz Lee, Xiangnan Kong, Yihan Bao, Constance M. Moore
2017	A*	`conf`	Kernel-Based Feature Extraction for Collaborative Filtering. ICDM Saket Sathe, Charu C. Aggarwal, Xiangnan Kong, Xinyue Liu
2017	A	`conf`	Learning Node Embeddings in Interaction Graphs. CIKM Yao Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu
2017	A	`conf`	Meta-Path Graphical Lasso for Learning Heterogeneous Connectivities. SDM Yao Zhang, Yun Xiong, Xinyue Liu, Xiangnan Kong, Yangyong Zhu
2017	J	`jnl`	Representation Learning in Large Attributed Graphs. CoRR Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Hoda Eldardiry
2017	A	`conf`	Unified and Contrasting Graphical Lasso for Brain Network Discovery. SDM Xinyue Liu, Xiangnan Kong, Ann B. Ragin
2017	—	`conf`	Using Social Sensing to Discover Trends in Public Emotion. ICSC Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu
2016	J	`jnl`	Badge System Analysis and Design. CoRR Jiawei Zhang, Xiangnan Kong, Philip S. Yu
2016	B	`conf`	Bermuda: An Efficient MapReduce Triangle Listing Algorithm for Web-Scale Graphs. SSDBM Dongqing Xiao, Mohamed Y. Eltabakh, Xiangnan Kong
2016	A	`conf`	Collective Traffic Prediction with Partially Observed Traffic History using Location-Based Social Media. CIKM Xinyue Liu, Xiangnan Kong, Yanhua Li
2016	A	`conf`	Kernelized Matrix Factorization for Collaborative Filtering. SDM Xinyue Liu, Charu C. Aggarwal, Yufeng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe
2016	A*	`conf`	NetCycle: Collective Evolution Inference in Heterogeneous Information Networks. KDD Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu
2016	B	`conf`	Social badge system analysis. ASONAM Jiawei Zhang, Xiangnan Kong, Philip S. Yu
2015	J	`jnl`	A review of heterogeneous data mining for brain disorder identification. Brain Informatics Bokai Cao, Xiangnan Kong, Philip S. Yu
2015	J	`jnl`	A review of heterogeneous data mining for brain disorders. CoRR Bokai Cao, Xiangnan Kong, Philip S. Yu
2015	J	`jnl`	CelebrityNet: A Social Network Constructed from Large-Scale Online Celebrity Images. ACM Trans. Multim. Comput. Commun. Appl. Li-Jia Li, David A. Shamma, Xiangnan Kong, Sina Jafarpour, Roelof van Zwol, Xuanhui Wang
2015	—	`conf`	Identification of Discriminative Subgraph Patterns in fMRI Brain Networks in Bipolar Affective Disorder. BIH Bokai Cao, Liang Zhan, Xiangnan Kong, Philip S. Yu, Nathalie Vizueta, Lori L. Altshuler, Alex D. Leow
2015	J	`jnl`	Identifying HIV-induced subgraph patterns in brain networks with side information. Brain Informatics Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu, Ann B. Ragin
2015	A*	`conf`	Mining Brain Networks Using Multiple Side Views for Neurological Disorder Identification. ICDM Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu, Ann B. Ragin
2015	J	`jnl`	Mining Brain Networks using Multiple Side Views for Neurological Disorder Identification. CoRR Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu, Ann B. Ragin
2015	Misc	`conf`	PNA: Partial Network Alignment with Generic Stable Matching. IRI Jiawei Zhang, Weixiang Shao, Senzhang Wang, Xiangnan Kong, Philip S. Yu
2015	J	`jnl`	Partial Network Alignment with Anchor Meta Path and Truncated Generic Stable Matching. CoRR Jiawei Zhang, Weixiang Shao, Senzhang Wang, Xiangnan Kong, Philip S. Yu
2015	—	`conf`	Python in Data Science Research and Education. SciPy Randy C. Paffenroth, Xiangnan Kong
2014	—	`ch.`	Active Learning: A Survey. Data Classification: Algorithms and Applications Charu C. Aggarwal, Xiangnan Kong, Quanquan Gu, Jiawei Han, Philip S. Yu
2014	A*	`conf`	Collective Prediction of Multiple Types of Links in Heterogeneous Information Networks. ICDM Bokai Cao, Xiangnan Kong, Philip S. Yu
2014	—	`conf`	Discovering Organizational Correlations from Twitter. ICDM Workshops Jingyuan Zhang, Xiaoxiao Shi, Xiangnan Kong, Hong-Han Shuai, Philip S. Yu
2014	J	`jnl`	Discovering Organizational Correlations from Twitter. CoRR Jingyuan Zhang, Xiaoxiao Shi, Xiangnan Kong, Hong-Han Shuai, Philip S. Yu
2014	A	`conf`	DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages. SDM Lifang He, Xiangnan Kong, Philip S. Yu, Xiaowei Yang, Ann B. Ragin, Zhifeng Hao
2014	J	`jnl`	DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages. CoRR Lifang He, Xiangnan Kong, Philip S. Yu, Ann B. Ragin, Zhifeng Hao, Xiaowei Yang
2014	J	`jnl`	HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. Chuan Shi, Xiangnan Kong, Yue Huang, Philip S. Yu, Bin Wu
2014	A	`conf`	Inferring the impacts of social media on crowdfunding. WSDM Chun-Ta Lu, Sihong Xie, Xiangnan Kong, Philip S. Yu
2014	A	`conf`	Large-Scale Multi-Label Learning with Incomplete Label Assignments. SDM Xiangnan Kong, Zhaoming Wu, Li-Jia Li, Ruofei Zhang, Philip S. Yu, Hang Wu, Wei Fan
2014	J	`jnl`	Large-Scale Multi-Label Learning with Incomplete Label Assignments. CoRR Xiangnan Kong, Zhaoming Wu, Li-Jia Li, Ruofei Zhang, Philip S. Yu, Hang Wu, Wei Fan
2014	A*	`conf`	Low-Density Cut Based Tree Decomposition for Large-Scale SVM Problems. ICDM Lifang He, Hong-Han Shuai, Xiangnan Kong, Zhifeng Hao, Xiaowei Yang, Philip S. Yu
2014	J	`jnl`	Multi-Label Classification Based on Multi-Objective Optimization. ACM Trans. Intell. Syst. Technol. Chuan Shi, Xiangnan Kong, Di Fu, Philip S. Yu, Bin Wu
2014	A	`conf`	NCR: A Scalable Network-Based Approach to Co-Ranking in Question-and-Answer Sites. CIKM Jingyuan Zhang, Xiangnan Kong, Roger Jie Luo, Yi Chang, Philip S. Yu
2014	J	`jnl`	Privacy Preserving Social Network Publication Against Mutual Friend Attacks. CoRR Chong-Jing Sun, Philip S. Yu, Xiangnan Kong, Yan Fu
2014	J	`jnl`	Privacy Preserving Social Network Publication Against Mutual Friend Attacks. Trans. Data Priv. Chong-Jing Sun, Philip S. Yu, Xiangnan Kong, Yan Fu
2014	A*	`conf`	Tensor-Based Multi-view Feature Selection with Applications to Brain Diseases. ICDM Bokai Cao, Lifang He, Xiangnan Kong, Philip S. Yu, Zhifeng Hao, Ann B. Ragin
2014	A	`conf`	Transferring heterogeneous links across location-based social networks. WSDM Jiawei Zhang, Xiangnan Kong, Philip S. Yu
2014	—	`conf`	Visual Recognition by Exploiting Latent Social Links in Image Collections. MMM (1) Li-Jia Li, Xiangnan Kong, Philip S. Yu
2014	A	`conf`	When and Where: Predicting Human Movements Based on Social Spatial-Temporal Events. SDM Ning Yang, Xiangnan Kong, Fengjiao Wang, Philip S. Yu
2014	J	`jnl`	When and Where: Predicting Human Movements Based on Social Spatial-Temporal Events. CoRR Ning Yang, Xiangnan Kong, Fengjiao Wang, Philip S. Yu
2013	J	`jnl`	Brain network analysis: a data mining perspective. SIGKDD Explor. Xiangnan Kong, Philip S. Yu
2013	J	`jnl`	Discriminative Feature Selection for Uncertain Graph Classification CoRR Xiangnan Kong, Philip S. Yu, Xue Wang, Ann B. Ragin
2013	A	`conf`	Discriminative Feature Selection for Uncertain Graph Classification. SDM Xiangnan Kong, Ann B. Ragin, Xue Wang, Philip S. Yu
2013	J	`jnl`	HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks. CoRR Chuan Shi, Xiangnan Kong, Yue Huang, Philip S. Yu, Bin Wu
2013	A	`conf`	Inferring anchor links across multiple heterogeneous social networks. CIKM Xiangnan Kong, Jiawei Zhang, Philip S. Yu
2013	J	`jnl`	Meta Path-Based Collective Classification in Heterogeneous Information Networks CoRR Xiangnan Kong, Bokai Cao, Philip S. Yu, Ying Ding, David J. Wild
2013	A*	`conf`	Multi-label classification by mining label and instance correlations from heterogeneous information networks. KDD Xiangnan Kong, Bokai Cao, Philip S. Yu
2013	A*	`conf`	Multilabel Consensus Classification. ICDM Sihong Xie, Xiangnan Kong, Jing Gao, Wei Fan, Philip S. Yu
2013	J	`jnl`	Multilabel Consensus Classification. CoRR Sihong Xie, Xiangnan Kong, Jing Gao, Wei Fan, Philip S. Yu
2013	A*	`conf`	Predicting Social Links for New Users across Aligned Heterogeneous Social Networks. ICDM Jiawei Zhang, Xiangnan Kong, Philip S. Yu
2013	J	`jnl`	Predicting Social Links for New Users across Aligned Heterogeneous Social Networks. CoRR Jiawei Zhang, Xiangnan Kong, Philip S. Yu
2013	J	`jnl`	Predicting Trends in Social Networks via Dynamic Activeness Model. CoRR Shuyang Lin, Xiangnan Kong, Philip S. Yu
2013	A	`conf`	Predicting trends in social networks via dynamic activeness model. CIKM Shuyang Lin, Xiangnan Kong, Philip S. Yu
2013	—	`conf`	Privacy Preserving Social Network Publication against Mutual Friend Attacks. ICDM Workshops Chong-Jing Sun, Philip S. Yu, Xiangnan Kong, Yan Fu
2013	J	`jnl`	Transductive Multilabel Learning via Label Set Propagation. IEEE Trans. Knowl. Data Eng. Xiangnan Kong, Michael K. Ng, Zhi-Hua Zhou
2012	A*	`conf`	Community detection in incomplete information networks. WWW Wangqun Lin, Xiangnan Kong, Philip S. Yu, Quanyuan Wu, Yan Jia, Chuan Li
2012	A*	`conf`	HeteRecom: a semantic-based recommendation systemin heterogeneous networks. KDD Chuan Shi, Chong Zhou, Xiangnan Kong, Philip S. Yu, Gang Liu, Bai Wang
2012	A	`conf`	Meta path-based collective classification in heterogeneous information networks. CIKM Xiangnan Kong, Philip S. Yu, Ying Ding, David J. Wild
2012	—	`conf`	Monitoring knowledge flow through scholarly networks. ASIST Erjia Yan, Ying Ding, Xiangnan Kong
2012	A	`conf`	Multi-Objective Multi-Label Classification. SDM Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang
2012	B	`conf`	Relevance search in heterogeneous networks. EDBT Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie, Bin Wu
2012	A	`conf`	Transfer Significant Subgraphs across Graph Databases. SDM Xiaoxiao Shi, Xiangnan Kong, Philip S. Yu
2012	J	`jnl`	gMLC: a multi-label feature selection framework for graph classification. Knowl. Inf. Syst. Xiangnan Kong, Philip S. Yu
2011	C	`conf`	An ensemble-based approach to fast classification of multi-label data streams. CollaborateCom Xiangnan Kong, Philip S. Yu
2011	A*	`conf`	Dual active feature and sample selection for graph classification. KDD Xiangnan Kong, Wei Fan, Philip S. Yu
2011	A	`conf`	Multi-Label Collective Classification. SDM Xiangnan Kong, Xiaoxiao Shi, Philip S. Yu
2011	—	`conf`	Multi-label Ensemble Learning. ECML/PKDD (3) Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang
2011	A*	`conf`	Positive and Unlabeled Learning for Graph Classification. ICDM Yuchen Zhao, Xiangnan Kong, Philip S. Yu
2010	A*	`conf`	Multi-label Feature Selection for Graph Classification. ICDM Xiangnan Kong, Philip S. Yu
2010	A*	`conf`	Semi-supervised feature selection for graph classification. KDD Xiangnan Kong, Philip S. Yu