Xiangnan Kong

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 102

Top Venues

Publications

Jidapa Thadajarassiri, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner
Amalgamating Multi-Task Models with Heterogeneous Architectures. AAAI (2024)
Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong
Multi-State Brain Network Discovery. BigData (2023)
Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong
One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. KDD (2023)
Jidapa Thadajarassiri, Thomas Hartvigsen, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner
Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer. AAAI (2023)
Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong
Multi-State Brain Network Discovery. CoRR (2023)
Jianjun Luo, Ryan A. Rossi, Xiangnan Kong, Yanhua Li
Multi-Item Continuous Influence Maximization. BigData (2023)
Thomas Hartvigsen, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner
Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks. CoRR (2023)
Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong
One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. CoRR (2023)
Yao Su, Xin Dai, Lifang He, Xiangnan Kong
ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. CoRR (2022)
Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner
Stop&Hop: Early Classification of Irregular Time Series. CIKM (2022)
Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong
ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. CoRR (2022)
Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
Off-Deployment Traffic Estimation - A Traffic Generative Adversarial Networks Approach. IEEE Trans. Big Data 8 (4) (2022)
Nesreen K. Ahmed, Ryan A. Rossi, John Boaz Lee, Theodore L. Willke, Rong Zhou, Xiangnan Kong, Hoda Eldardiry
Role-Based Graph Embeddings. IEEE Trans. Knowl. Data Eng. 34 (5) (2022)
Yao Su, Xin Dai, Lifang He, Xiangnan Kong
ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. ICDM (2022)
Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation. ICDM (2022)
Yao Zhang, Sijia Peng, Yun Xiong, Xiangnan Kong, Xinyue Liu, Yangyong Zhu
Multi-task attributed graphical lasso and its application in fund classification. World Wide Web 25 (3) (2022)
Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner
Stop&Hop: Early Classification of Irregular Time Series. CoRR (2022)
Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong
ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. KDD (2022)
Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Aditya Arora, Jihane Zouaoui
One-Shot Learning on Attributed Sequences. CoRR (2022)
Hang Yin, Xinyue Liu, Xiangnan Kong
Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks. CoRR (2021)
Hang Yin, John Boaz Lee, Xiangnan Kong, Thomas Hartvigsen, Sihong Xie
Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks. KDD (2021)
Yun Xiong, Yizhou Zhang, Xiangnan Kong, Huidi Chen, Yangyong Zhu
GraphInception: Convolutional Neural Networks for Collective Classification in Heterogeneous Information Networks. IEEE Trans. Knowl. Data Eng. 33 (5) (2021)
Samuel S. Ogden, Xiangnan Kong, Tian Guo
PieSlicer: Dynamically Improving Response Time for Cloud-based CNN Inference. ICPE (2021)
Dongyu Zhang, Cansu Sen, Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
Human-like Explanation for Text Classification With Limited Attention Supervision. IEEE BigData (2021)
Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie
Self-learn to Explain Siamese Networks Robustly. ICDM (2021)
Yao Zhang, Yun Xiong, Xiangnan Kong, Zhuang Niu, Yangyong Zhu
IGE+: A Framework for Learning Node Embeddings in Interaction Graphs. IEEE Trans. Knowl. Data Eng. 33 (3) (2021)
Xin Dai, Xiangnan Kong, Tian Guo, Yixian Huang
CiNet: Redesigning Deep Neural Networks for Efficient Mobile-Cloud Collaborative Inference. SDM (2021)
Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie
Self-learn to Explain Siamese Networks Robustly. CoRR (2021)
Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
Semi-Supervised Knowledge Amalgamation for Sequence Classification. AAAI (2021)
Xin Dai, Xiangnan Kong, Tian Guo, Xinlu He
FiShNet: Fine-Grained Filter Sharing for Resource-Efficient Multi-Task Learning. CIKM (2021)
Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
Learning Similarity-Preserving Meta-Embedding for Text Mining. IEEE BigData (2020)
Xin Dai, Xiangnan Kong, Tian Guo, John Boaz Lee, Xinyue Liu, Constance M. Moore
Recurrent Networks for Guided Multi-Attention Classification. KDD (2020)
Xin Dai, Xiangnan Kong, Tian Guo
EPNet: Learning to Exit with Flexible Multi-Branch Network. CIKM (2020)
Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner
Learning to Selectively Update State Neurons in Recurrent Networks. CIKM (2020)
Yun Xiong, Shaofeng Xu, Keyao Rong, Xinyue Liu, Xiangnan Kong, Shanshan Li, Philip S. Yu, Yangyong Zhu
Code2Text: Dual Attention Syntax Annotation Networks for Structure-Aware Code Translation. DASFAA (3) (2020)
Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. KDD (2020)
Cansu Sen, Thomas Hartvigsen, Biao Yin, Xiangnan Kong, Elke A. Rundensteiner
Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words? ACL (2020)
Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
MLAS: Metric Learning on Attributed Sequences. IEEE BigData (2020)
Hang Yin, Xinyue Liu, Xiangnan Kong
Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks. IEEE BigData (2020)
Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin
Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks. Inf. Process. Manag. 57 (6) (2020)
Yao Zhang, Yun Xiong, Xiangnan Kong, Xinyue Liu, Yangyong Zhu
Multi-task Attributed Graphical Lasso. APWeb/WAIM (1) (2020)
Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke A. Rundensteiner
A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events. EMNLP (Findings) (2020)
Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner
Recurrent Halting Chain for Early Multi-label Classification. KDD (2020)
John Boaz Lee, Xiangnan Kong, Constance M. Moore, Nesreen K. Ahmed
Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions. SDM (2020)
Xin Dai, Xiangnan Kong, Xinyue Liu, John Boaz Lee, Constance M. Moore
Dual-Attention Recurrent Networks for Affine Registration of Neuroimaging Data. SDM (2020)
Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
MLAS: Metric Learning on Attributed Sequences. CoRR (2020)
Xiao Qin, Cao Xiao, Tengfei Ma, Tabassum Kakar, Susmitha Wunnava, Xiangnan Kong, Elke A. Rundensteiner, Fei Wang
Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding. IEEE BigData (2020)
Yuyan Zheng, Chuan Shi, Xiangnan Kong, Yanfang Ye
Author Set Identification via Quasi-Clique Discovery. CIKM (2019)
Thanh Tran, Xinyue Liu, Kyumin Lee, Xiangnan Kong
Signed Distance-based Deep Memory Recommender. WWW (2019)
Yafang Li, Caiyan Jia, Xiangnan Kong, Liu Yang, Jian Yu
Locally Weighted Fusion of Structural and Attribute Information in Graph Clustering. IEEE Trans. Cybern. 49 (1) (2019)
Jianjun Luo, Xinyue Liu, Xiangnan Kong
Competitive opinion maximization in social networks. ASONAM (2019)
Thanh Tran, Xinyue Liu, Kyumin Lee, Xiangnan Kong
Signed Distance-based Deep Memory Recommender. CoRR (2019)
Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
Attributed Sequence Embedding. CoRR (2019)
John Boaz Lee, Ryan A. Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao
Graph Convolutional Networks with Motif-based Attention. CIKM (2019)
Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Jihane Zouaoui, Aditya Arora
Attributed Sequence Embedding. IEEE BigData (2019)
Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo
TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks. ICDM (2019)
Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner
AMAS: Attention Model for Attributed Sequence Classification. SDM (2019)
John Boaz Lee, Xiangnan Kong
Learning compact graph representations via an encoder-decoder network. Appl. Netw. Sci. 4 (1) (2019)
Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner
Adaptive-Halting Policy Network for Early Classification. KDD (2019)
Yao Zhang, Yun Xiong, Lu Ruan, Xiangnan Kong, Yangyong Zhu
NetMerger: Predicting Cross-network Links in Merged Heterogeneous Networks. WI (Companion) (2019)
Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining. BHI (2019)
Shaofeng Xu, Yun Xiong, Xiangnan Kong, Yangyong Zhu
Net2Text: An Edge Labelling Language Model for Personalized Review Generation. DASFAA (1) (2019)
Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention. IEEE BigData (2019)
Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner
Learning Temporal Relevance in Longitudinal Medical Notes. IEEE BigData (2019)
Hang Yin, Xiangnan Kong, Xinyue Liu
Coherent Graphical Lasso for Brain Network Discovery. ICDM (2018)
Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu
Tracking Dynamic Magnet Communities: Insights from a Network Perspective. DASFAA (1) (2018)
Xinyue Liu, Xiangnan Kong, Lei Liu, Kuorong Chiang
TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks. CoRR (2018)
Nesreen K. Ahmed, Ryan A. Rossi, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Rong Zhou, Hoda Eldardiry
Learning Role-based Graph Embeddings. CoRR (2018)
Yun Xiong, Yizhou Zhang, Xiangnan Kong, Yangyong Zhu
NetCycle+: A Framework for Collective Evolution Inference in Dynamic Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 30 (8) (2018)
Xinyue Liu, Xiangnan Kong, Lei Liu, Kuorong Chiang
TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks. ICDM (2018)
Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Aditya Arora, Jihane Zouaoui
One-Shot Learning on Attributed Sequences. IEEE BigData (2018)
Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke A. Rundensteiner, Sanjay K. Sahoo, Suranjan De
One Size Does Not Fit All: An Ensemble Approach Towards Information Extraction from Adverse Drug Event Narratives. HEALTHINF (2018)
Yun Xiong, Lu Ruan, Mengjie Guo, Chunlei Tang, Xiangnan Kong, Yangyong Zhu, Wei Wang
Predicting Disease-related Associations by Heterogeneous Network Embedding. BIBM (2018)
Thomas Hartvigsen, Cansu Sen, Sarah Brownell, Erin Teeple, Xiangnan Kong, Elke A. Rundensteiner
Early Prediction of MRSA Infections using Electronic Health Records. HEALTHINF (2018)
John Boaz Lee, Ryan A. Rossi, Xiangnan Kong
Graph Classification using Structural Attention. KDD (2018)
John Boaz Lee, Ryan A. Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao
Higher-order Graph Convolutional Networks. CoRR (2018)
Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Elke A. Rundensteiner, Xiangnan Kong
Deep Learning Strategies for Automatic Detection of Medication and Adverse Drug Events from Electronic Health Records. AMIA (2018)
Dongqing Xiao, Mohamed Y. Eltabakh, Xiangnan Kong
Sharing Uncertain Graphs Using Syntactic Private Graph Models. ICDE (2018)
Xinyue Liu, Xiangnan Kong, Philip S. Yu
Active Opinion Maximization in Social Networks. KDD (2018)
Yafang Li, Xiangnan Kong, Caiyan Jia, Jianqiang Li
Clustering Uncertain Graphs with Node Attributes. ACML (2018)
Yizhou Zhang, Yun Xiong, Xiangnan Kong, Shanshan Li, Jinhong Mi, Yangyong Zhu
Deep Collective Classification in Heterogeneous Information Networks. WWW (2018)
Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Elke A. Rundensteiner, Xiangnan Kong
Bidirectional LSTM-CRF for Adverse Drug Event Tagging in Electronic Health Records. Medication and Adverse Drug Event Detection (2018)
Chang Liao, Yun Xiong, Xiangnan Kong, Yangyong Zhu, Shimin Zhao, Shanshan Li
Functional-Oriented Relationship Strength Estimation: From Online Events to Offline Interactions. DASFAA (1) (2018)
Susmitha Wunnava, Xiao Qin, Tabassum Kakar, M. L. Tlachac, Xiangnan Kong, Elke A. Rundensteiner, Sanjay K. Sahoo, Suranjan De
Multi-layered Learning for Information Extraction from Adverse Drug Event Narratives. BIOSTEC (Selected Papers) (2018)
Xinyue Liu, Yuanfang Song, Charu C. Aggarwal, Yao Zhang, Xiangnan Kong
BiCycle: Item Recommendation with Life Cycles. ICDM (2017)
Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Hoda Eldardiry
Representation Learning in Large Attributed Graphs. CoRR (2017)
Yao Zhang, Yun Xiong, Xinyue Liu, Xiangnan Kong, Yangyong Zhu
Meta-Path Graphical Lasso for Learning Heterogeneous Connectivities. SDM (2017)
Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Hoda Eldardiry
A Framework for Generalizing Graph-based Representation Learning Methods. CoRR (2017)
Xinyue Liu, Xiangnan Kong, Ann B. Ragin
Unified and Contrasting Graphical Lasso for Brain Network Discovery. SDM (2017)
Yao Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu
Learning Node Embeddings in Interaction Graphs. CIKM (2017)
Xinyue Liu, Xiangnan Kong, Philip S. Yu
Collective discovery of brain networks with unknown groups. IJCNN (2017)
John Boaz Lee, Xiangnan Kong, Yihan Bao, Constance M. Moore
Identifying Deep Contrasting Networks from Time Series Data: Application to Brain Network Analysis. SDM (2017)
Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu
Discover trends in public emotion using social sensing. SIGWEB Newsl. 2017 (Spring) (2017)
John Boaz Lee, Ryan A. Rossi, Xiangnan Kong
Deep Graph Attention Model. CoRR (2017)
Maryam Hasan, Elke A. Rundensteiner, Xiangnan Kong, Emmanuel Agu
Using Social Sensing to Discover Trends in Public Emotion. ICSC (2017)
Saket Sathe, Charu C. Aggarwal, Xiangnan Kong, Xinyue Liu
Kernel-Based Feature Extraction for Collaborative Filtering. ICDM (2017)
Xinyue Liu, Charu C. Aggarwal, Yu-Feng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe
Kernelized Matrix Factorization for Collaborative Filtering. SDM (2016)
Xinyue Liu, Xiangnan Kong, Yanhua Li
Collective Traffic Prediction with Partially Observed Traffic History using Location-Based Social Media. CIKM (2016)
Jiawei Zhang, Xiangnan Kong, Philip S. Yu
Badge System Analysis and Design. CoRR (2016)
Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu
NetCycle: Collective Evolution Inference in Heterogeneous Information Networks. KDD (2016)

Xiangnan Kong.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Xiangnan Kong