Yizhou Sun

Publications

[DBLP] [Google Scholar]

Book

• Yizhou Sun and Jiawei Han, Mining Heterogeneous Information Networks: Principles and Methodologies, Morgan & Claypool Publishers, 2012.

Book Chapters

• Hongbo Deng, Yizhou Sun, Yi Chang, and Jiawei Han, "Probabilistic Models for Classification," in Charu C. Aggarwal (eds.), Data Classification: Algorithms and Applications, CRC Press, 2013, pp. 54-74.
• Yizhou Sun and Jiawei Han, "Ranking Methods for Networks," accepted by Encyclopedia of Social Network Analysis and Mining, Springer, June 2013.
• Yang Yang, Yizhou Sun, Saurav Pandit, Nitesh V. Chawla, and Jiawei Han, "Prospective on Measurement Metrics for Community Detection Algorithms," in Tansel Ozyer, Zeki Erdem, Jon Rokne and Suheil Khoury (eds.), Mining Social Networks and Security Informatics, Springer, 2013, pp. 227-242.
• Yizhou Sun, Hongbo Deng and Jiawei Han, "Probabilistic Models for Text Mining", in Charu C. Aggarwal and ChengXiang Zhai (eds.), Mining Text Data, Kluwer Academic Publishers, 2012, pp. 257-294.
• Yizhou Sun and Jiawei Han, "Integrating Clustering and Ranking for Heterogeneous Information Network Analysis", in Philip S. Yu, Jiawei Han and Christos Faloutsos (eds.), Link Mining: Models, Algorithms and Applications, Springer, 2010, pp. 439-474.

Conferences/Journals

2024

• Roshni Iyer, YEWEN WANG, Wei Wang, Yizhou Sun, Non-Euclidean Mixture Model for Social Network Embedding, NeurIPS'24.
• Arjun Subramonian, Jian Kang, Yizhou Sun, Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks, NeurIPS'24.
• Arvind Murari Vepa, ZUKANG YANG, Andrew Choi, Jungseock Joo, Fabien Scalzo, Yizhou Sun, Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation, NeurIPS'24.
• Zijie Huang, Wanjia Zhao, Jingdong Gao, Ziniu Hu, Xiao Luo, Yadi Cao, Yuanzhou Chen, Yizhou Sun, Wei Wang, Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling, NeurIPS'24.
• Kaiqiao Han, Yi Yang, Zijie Huang, Xuan Kan, Ying Guo, Yang Yang, Lifang He, Liang Zhan, Yizhou Sun, Wei Wang, Carl Yang, BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations, Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), 2024.
• Kewei Cheng, Nesreen K. Ahmed, Theodore L. Willke, Yizhou Sun, Structure Guided Prompt: Instructing Large Language Model in Multi-Step Reasoning by Exploring Graph Structure of the Text, EMNLP'24.
• Zongyu Lin, Zhikun Xu, Yixin Wan, Stuart X. Yao, Xiaohan Song, Tsung-Han Lin, Selina Song, Pranav Subbaraman, Kai-Wei Chang, Yizhou Sun, VISUAL-ALPHASOCIAL: Benchmark and Self-Reflective Chain-of-Thought Generation for Visual Social Commonsense Reasoning, EMNLP 2024 Findings.
• Kewei Cheng, Nesreen K. Ahmed, Ryan A. Rossi, Theodore Willke, Yizhou Sun, Neural-Symbolic Methods for Knowledge Graph Reasoning: A Survey, TKDE.
• Yunsheng Bai, Atefeh Sohrabizadeh, Zijian Ding, Rongjian Liang, Weikai Li, Ding Wang, Haoxing Ren, Yizhou Sun, Jason Cong. Learning to Compare Hardware Designs for High-Level Synthesis. 2024 ACM/IEEE International Symposium on Machine Learning for CAD (MLCAD '24), September 9–11, 2024, Salt Lake City, UT, USA. ACM, New York, NY, USA, 7 pages.
• Zongyue Qin, Yunsheng Bai, Atefeh Sohrabizadeh, Zijian Ding, Ziniu Hu, Yizhou Sun, Jason Cong. Cross-Modality Program Representation Learning for Electronic Design Automation with High-Level Synthesis. ACM/IEEE International Symposium on Machine Learning for CAD (MLCAD ’24), September 9–11, 2024, Salt Lake City, UT, USA. ACM, New York, NY, USA, 12 pages.
• Zijian Ding, Atefeh Sohrabizadeh, Weikai Li, Zongyue Qin, Yizhou Sun, Jason Cong, Efficient Task Transfer for HLS DSE, ICCAD'24
• Fred Xu, Song Jiang, Zijie Huang, Xiao Luo, Shichang Zhang, Yuanzhou Chen, Yizhou Sun, FUSE: Measure-Theoretic Compact Fuzzy Set Representation for Taxonomy Expansion, ACL 2024 Findings.
• Xiao Luo, Yiyang Gu, Huiyu Jiang, Hang Zhou, Jinsheng Huang, Wei Ju, Zhiping Xiao, Ming Zhang, Yizhou Sun, PGODE: Towards High-quality System Dynamics Modeling, ICML'24.
• Arjun Subramonian, Levent Sagun, Yizhou Sun, Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction, ICML'24.
• Xiaoxuan Wang, Ziniu Hu, Pan Lu, Yanqiao Zhu, Jieyu Zhang, Satyen Subramaniam, Arjun R Loomba, Shichang Zhang, Yizhou Sun, Wei Wang, SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models, ICML'24.
• Haoyu Li, Shichang Zhang, Longwen Tang, Mathieu Bauchy, Yizhou Sun, Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks, ICML'24.
• Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, Asli Celikyilmaz, RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models, NAACL'24.
• Chunheng Jiang, Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Yizhou Sun, Jianxi Gao, Network Properties Determine Neural Network Performance, Nature Communications, 2024.
• Zijie Huang, Jeehyun Hwang, Junkai Zhang, Jinwoo Baik, Weitong Zhang, Dominik Wodarz, Yizhou Sun, Quanquan Gu and Wei Wang, Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems, TheWebConf'24, May 2024.
• Weikai Li, Patricia Xiao, Xiao Luo, Fast Inference of Removal-Based Node Influence, TheWebConf'24, May 2024.
• Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang, Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks, ICLR'24, May 2024.
• Yewen Wang, Shichang Zhang, John Cho, Yizhou Sun, Laplacian Score Benefit Adaptive Filter Selection for Graph Neural Networks, SDM'24, April 2024.
• Shichang Zhang, Ziniu Hu, Arjun Subramonian, Yizhou Sun, Motif-Driven Contrastive Learning of Graph Representations, TKDE, Feb. 2024.

2023

• Xiao Luo, Haixin Wang, Zijie Huang, Huiyu Jiang, Abhijeet Sadashiv Gangan, Song Jiang, Yizhou Sun, CARE: Modeling Interacting Dynamics Under Temporal Distribution Shift, NeurIPS 2023.
• Ziniu Hu, Ahmet Iscen, Chen Sun, Kai-Wei Chang, Yizhou Sun, Cordelia Schmid, David A Ross, Alireza Fathi, AVIS: Autonomous Visual Information Seeking with Large Language Models, NeurIPS 2023.
• Yunsheng Bai, Atefeh Sohrabizadeh, Zongyue Qin, Ziniu Hu, Yizhou Sun, Jason Cong, Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs, NeurIPS 2023.
• Xiao Luo, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun, RIGNN: A Rationale Perspective for Semi-supervised Open-world Graph Classification, TMLR, 2023.
• Atefeh Sohrabizadeh, Yunsheng Bai, Yizhou Sun, Jason Cong, "Robust GNN-based Representation Learning for HLS", IEEE/ACM ICCAD'23. (Best Paper Award candidate)
• Han Liu, Zijie Huang, Samuel S. Schoenholz, Ekin D. Cubuk, Morten M. Smedskjaer, Yizhou Sun, Wei Wang and Mathieu Bauchy. Learning molecular dynamics: predicting the dynamics of glasses by a machine learning simulator. Materials Horizons, June 2023.
• Zhiping Xiao, Jeffery Zhu, Yining Wang, Pei Zhou, Wen Hong Lam, Mason A. Porter, Yizhou Sun. Detecting Political Biases of Named Entities and Hashtags on Twitter. EPJ Data Science.
• Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun. HOPE: High-order Graph ODE For Modeling Interacting Dynamics. ICML 2023.
• Zijie Huang, Daheng Wang, Binxuan Huang, Chenwei Zhang, Jingbo Shang, Yan Liang, Zhengyang Wang, Xian Li, Christos Faloutsos, Yizhou Sun and Wei Wang. Concept2Box: Joint Geometric Embeddings for Learning Two-View Knowledge Graphs. ACL Findings 2023.
• Derek Xu, Shuyan Dong, Changhan Wang, Suyoun Kim, Zhaojiang Lin, Bing Liu, Akshat Shrivastava, Shang-Wen Li, Liang-Hsuan Tseng, Guan-Ting Lin, Alexei Baevski, Hung-yi Lee, Yizhou Sun and Wei Wang. Introducing Semantics into Speech Encoders. ACL 2023.
• Kewei Cheng, Xian Li, Zhengyang Wang, Chenwei Zhang, Binxuan Huang, Yifan Ethan Xu, Xin Luna Dong and Yizhou Sun. Tab-Cleaner: Weakly Supervised Tabular Data Cleaning via Pre-training for E-commerce Catalog. ACL 2023, Industry Track.
• Zijie Huang, Yizhou Sun, Wei Wang. Generalizing Graph ODE for Learning Complex System Dynamics across Environments. KDD 2023. [Video]
• Song Jiang, Zijie Huang, Xiao Luo, Yizhou Sun. CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems. KDD 2023. [Video]
• Tong Wang, Xu-Wen Wang, Kathleen A. Lee-Sarwar, Augusto A. Litonjua, Scott T. Weiss, Yizhou Sun, Sergei Maslov, and Yang-Yu Liu, "Predicting metabolomic profiles from microbial composition through neural ordinary differential equations," Nature Machine Intelligence, March 2023.
• Ziniu Hu, Ahmet Iscen, Chen Sun, Zirui Wang, Kai-Wei Chang, Yizhou Sun, Cordelia Schmid, David A Ross and Alireza Fathi, "REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory," In Proc. of the Conference on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 2023.
• Changjun Fan, Mutian Shen, Zohar Nussinov, Zhong Liu, Yizhou Sun, Yang-Yu Liu, "Searching for spin glass ground states through deep reinforcement learning," Nature Communications 2023, 14:725.
• Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos and Yizhou Sun, "PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction," in Proc. of The Web Conf. 2023, Austin, TX, Apr. 2023.
• Song Jiang, Qiyue Yao, Qifan Wang and Yizhou Sun, "A Vector Is Not Enough: Taxonomy Expansion via Box Embeddings," in Proc. of The Web Conf. 2023, Austin, TX, Apr. 2023. (Best Student Paper Award, top 2 among 1800+ submissions)
• Yiqiao Jin, Yunsheng Bai, Yanqiao Zhu, Yizhou Sun and Wei Wang, "Code Recommendation for Open Source Software Developers," in Proc. of The Web Conf. 2023, Austin, TX, Apr. 2023.
• Roshni G. Iyer, Thuy Vu, Alessandro Moschitti and Yizhou Sun, "Question-Answer Sentence Graph for Joint Modeling Answer Selection," in Proc. of 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL'23), Dubrovnik, Croatia, May. 2023.
• Kewei Cheng, Nesreen Ahmed, Yizhou Sun, "Neural Compositional Rule Learning for Knowledge Graph Reasoning," in Proc. of 2023 Int. Conf. on Learning Representations (ICLR’23), Kigali, Rwanda, May. 2023.
• Yiqiao Jin, Xiting Wang, Yaru Hao, Yizhou Sun, and Xing Xie, "Prototypical Fine-tuning: Towards Robust Performance Under Varying Data Sizes," in Proc. of the 37th AAAI Conf. on Artificial Intelligence (AAAI'23), Washington, DC, Feb. 2023.

2022

• Ziniu Hu, Yichong Xu, Wenhao Yu, Shuohang Wang, Ziyi Yang, Chenguang Zhu, Kai-Wei Chang and Yizhou Sun, "Empowering Language Models with Knowledge Graph Reasoning for Open-Domain Question Answering,"in Proc. 2022 Conf. on Empirical Methods in Natural Language Processing (EMNLP'22), Abu Dhabi, UAE, Dec. 2022.
• Arjun Subramonian, Kai-Wei Chang, and Yizhou Sun. " On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs," in Proc. of Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS'22), New Orleans, LA, Nov. 2022.
• Shichang Zhang, Neil Shah, Yozen Liu, and Yizhou Sun. "Explaining Graph Neural Networks with Structure-Aware Cooperative Games," in Proc. of Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS'22), New Orleans, LA, Nov. 2022.
• Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, and Ed H. Chi. "Improving Multi-Task Generalization via Regularizing Spurious Correlation," in Proc. of Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS'22), New Orleans, LA, Nov. 2022.
• Hongwei Wang, Zixuan Zhang, Sha Li, Jiawei Han, Yizhou Sun, Hanghang Tong, Joseph Olive, and Heng Ji. "Schema-Guided Event Graph Completion," in Proc. of 4th Conference on Automated Knowledge Base Construction (AKBC'22), London, UK, Nov. 2022.
• Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S. Yu, and Tianyi Wu. "Heterogeneous Information Networks: the Past, the Present, and the Future," in Proc. of VLDB Endow 15(12): 3807-3811 (2022)(VLDB'22), Sydney, Australia, Sept. 2022. (VLDB Test of Time Award Invited Paper)
• Song Jiang, Tahin Syed, Xuan Zhu, Joshua Levy, Boris Aronchik, Yizhou Sun. "Bridging Self-Attention and Time Series Decomposition for Periodic Forecasting," in Proc. of 31st ACM International Conference on Information and Knowledge Management (CIKM'22), Atlanta, GA, Oct. 2022.
• Song Jiang and Yizhou Sun. "Estimating Causal Effects on Networked Observational Data via Representation Learning," in Proc. of 31st ACM International Conference on Information and Knowledge Management (CIKM'22), Atlanta, GA, Oct. 2022.
• Junheng Hao, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Haifeng Chen, Junghwan Rhee, Zhichun Li and Wei Wang. "Multi-source Inductive Knowledge Graph Transfer, " in Proc. of Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD'22), Grenoble, France, Sept. 2022.
• Kewei Cheng, Jiahao Liu, Wei Wang, Yizhou Sun, "RLogic: Recursive Logical Rule Learning from Knowledge Graphs," in Proc. of 2022 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’22), Washington, DC, Aug. 2022.
• Roshni G. Iyer, Yusheng Bai, Wei Wang, Yizhou Sun, " Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs," in Proc. of 2022 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’22), Washington, DC, Aug. 2022.
• Yunsheng Bai, Atefeh Sohrabizadeh, Yizhou Sun, Jason Cong, "Improving GNN-Based Accelerator Design Automation with Meta Learning," in Proc. of 59th ACM/IEEE Design Automation Conference (DAC'22), San Francisco, July 2022.
• Atefeh Sohrabizadeh, Yunsheng Bai, Yizhou Sun, and Jason Cong, "Automated accelerator optimization aided by graph neural networks," in Proc. of 59th ACM/IEEE Design Automation Conference (DAC'22), San Francisco, July 2022.
• Zijie Huang, Zheng li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, and Wei Wang, "Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment," in Proc. of The 2022 Annual Meeting of the Association for Computational Linguistics (ACL’22), Dublin, Ireland, May 2022.
• Shichang Zhang, Yozen Liu, Yizhou Sun, and Neil Shah, "Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation," in Proc. 2022 Int. Conf. on Learning Representations (ICLR’22), April 2022. [Arxiv]
• Kewei Cheng, Xian Li, Yifan Xu, Xin Dong, and Yizhou Sun, "PGE: Product Graph Embedding Learning for Error Detection," PVLDB also Proc. of 48th International Conference on Very Large Data Bases (VLDB'22), Sydney, Australia, Sept. 2022. [Arxiv]
• Xuelu Chen, Ziniu Hu, and Yizhou Sun, "Fuzzy Logic based Logical Query Answering on Knowledge Graphs," in Proc. of the 36th AAAI Conf. on Artificial Intelligence (AAAI'22), Feb. 2022. [Slides][GitHub]
• Jiarong Xu, Yang Yang, Junru Chen, Xin Jiang, Chunping Wang, Jiangang Lu, and Yizhou Sun, "Unsupervised Adversarially Robust Representation Learning on Graphs," in Proc. of the 36th AAAI Conf. on Artificial Intelligence (AAAI'22), Feb. 2022.
• Jiarong Xu, Yizhou Sun, Xin Jiang, Yanhao Wang, Chunping Wang, Jiangang Lu, and Yang Yang, "Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs," in Proc. of the 36th AAAI Conf. on Artificial Intelligence (AAAI'22), Feb. 2022.
• Yiqiao Jin, Xiting Wang, Ruichao Yang, Yizhou Sun, Wei Wang, Hao Liao, and Xing Xie, "Towards Fine-Grained Reasoning for Fake News Detection," in Proc. of the 36th AAAI Conf. on Artificial Intelligence (AAAI'22), Feb. 2022.
• Michael Potter, Hamlin Liu, Yash Lala, Christian Loanzon, and Yizhou Sun, "GRU4RecBE: A Hybrid Session-Based Movie Recommendation System," in Proc. of the 36th AAAI Conf. on Artificial Intelligence (AAAI'22), Feb. 2022. (Student Abstract)

2021

• Roshni Iyer, Wei Wang, and Yizhou Sun, "Bi-Level Attention Graph Neural Networks," in Proc. 2021 IEEE Int. Conf. on Data Mining (ICDM'21), Dec. 2021.
• Kewei Cheng, Ziqing Yang, Ming Zhang, and Yizhou Sun, "UniKER: A Unified Framework for Combining Embedding and Definite Horn Rule Reasoning for Knowledge Graph Inference," in Proc. 2021 Conf. on Empirical Methods in Natural Language Processing (EMNLP'21), Nov. 2021. [GitHub]
• Ziniu Hu, Yizhou Sun and Kai-Wei Chang, "Relation-Guided Pre-Training for Open-Domain Question Answering," in Findings of EMNLP, 2021.
• Zijie Huang, Yizhou Sun, and Wei Wang, "Coupled Graph ODE for Learning Interacting System Dynamics," in Proc. of 2021 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'21), Aug. 2021. [GitHub]
• Junheng Hao, Chuan Lei, Vasilis Efthymiou, Abdul Quamar, Fatma Ozcan, Yizhou Sun, and Wei Wang, "MEDTO: Medical Data to Ontology Matching using Hybrid Graph Neural Networks," in Proc. of 2021 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'21), Aug. 2021.
• Yunsheng Bai*, Derek Xu*, Yizhou Sun, and Wei Wang, "GLSearch: Maximum Common Subgraph Detection via Learning to Search," in Proc. of Thirty-eighth International Conference on Machine Learning (ICML'21), July 2021. [Arxiv][GitHub](Spotlight)
• Yang Yang, Yuhong Xu, Yizhou Sun, Yuxiao Dong, Fei Wu, and Yueting Zhuang, "Mining Fraudsters and Fraudulent Strategies in Large-Scale Mobile Social Networks," IEEE Trans. Knowl. Data Eng. 33(1): 169-179, 2021.
• Yichao Zhou, Wei-Ting Chen, Bowen Zhang, David Lee, J. Harry Caufield, Kai-Wei Chang, Yizhou Sun, Peipei Ping, and Wei Wang, "CREATe: Clinical Report Extraction and Annotation Technology," IEEE 37rd International Conf. on Data Eng. (ICDE'21), Demo, April 2021.
• Xiang Li, Danhao Ding, Ben Kao, Yizhou Sun, and Nikos Mamoulis, "Leveraging Meta-path Contexts for Classification in Heterogeneous Information Networks," IEEE 37rd International Conf. on Data Eng. (ICDE'21), April 2021.
• Song Jiang, Bernard Koch, Yizhou Sun, "HINTS: Citation Time Series Prediction for New Publications via Dynamic Heterogeneous Information Network Embedding," in Proc. The Web Conf. 2021 (WWW’21), April 2021. [GitHub]
• Yichao Zhou, Yu Yan, Rujun Han, J. Harry Caufield, Kai-Wei Chang, Yizhou Sun, Peipei Ping, and Wei Wang, " Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference," in Proc. of the 35th AAAI Conf. on Artificial Intelligence (AAAI'21), Feb. 2021.

2020

• Carl Yang, Yuxin Xiao, Yu Zhang, Yizhou Sun and Jiawei Han, "Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark," in IEEE Transactions on Knowledge and Data Engineering, Dec. 2020.
• Zijie Huang, Yizhou Sun, Wei Wang, "Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations," in Thirty-fourth Conf. on Neural Information Processing Systems (NeurIPS'20), Dec. 2020. [Arxiv][GitHub]
• Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, and Wei Wang, "Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning," in Proc. 2020 IEEE Int. Conf. on Data Mining (ICDM'20), Nov. 2020 (Full Oral, Accept rate: 9.8%)
• Xuelu Chen, Muhao Chen, Changjun Fan, Ankith Uppunda, Yizhou Sun and Carlo Zaniolo, "Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer," in the 2020 Conf. on Empirical Methods in Natural Language Processing (Findings of EMNLP - 2020), Nov. 2020.
• Junheng Hao, Tong Zhao, Jin Li, Xin Luna Dong, Christos Faloutsos, Yizhou Sun and Wei Wang. “P-Companion: A Principled Framework for Diversified Complementary Product Recommendation”. In the 29th ACM Intl. Conf. on Information and Knowledge Management (CIKM'20), Applied Research Track. [Blog]
• Junheng Hao, Chelsea J.-T. Ju, Muhao Chen, Yizhou Sun, Carlo Zaniolo and Wei Wang. “Bio-JOIE: Joint Representation Learning of Biological Knowledge Bases”. In the 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB'20, Best Student Paper Award). [News]
• Ting Chen, Lala Li, Yizhou Sun, "Differentiable Product Quantization for Learning Compact Embedding Layers," in Proc. of Thirty-seventh International Conference on Machine Learning (ICML'20), July 2020.
• Ziniu Hu, Yuxiao Dong, Kuansan Wang, Kai-Wei Chang and Yizhou Sun, "GPT-GNN: Generative Pre-Training of Graph Neural Networks," in Proc. of 2020 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’20), San Diego, CA, August 2020. [GitHub]
• Zongyue Qin, Yunsheng Bai and Yizhou Sun, "GHashing: Semantic Graph Hashing for Approximate Similarity Search in Graph Databases," in Proc. of 2020 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’20), San Diego, CA, August 2020.
• Zhiping Xiao, Weiping Song, Haoyan Xu, Zhicheng Ren and Yizhou Sun, " TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding", in Proc. of 2020 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’20), San Diego, CA, August 2020. [GitHub]
• Yuxiao Dong, Ziniu Hu, Kuansan Wang, Yizhou Sun, Jie Tang, "Heterogeneous Network Representation Learning," (Survey Paper), in Proc. of 2020 Int. Joint Conf. on Artificial Intelligence and Pacific Rim Int. Conf. on Artificial Intelligence (IJCAI-PRICAI’20), Yokohoma, Japan, July 2020. [datasets]
• Changjun Fan, Zeng Li, Yizhou Sun*, Yang-Yu Liu*, "Finding key players in complex networks through deep reinforcement learning," Nature Machine Intelligence, May 2020. [GitHub]
• Ziniu Hu, Yuxiao Dong, Kuansan Wang, and Yizhou Sun, "Heterogeneous Graph Transformer," in Proc. 2020 Int. World Wide Web Conf. (WWW’20), Taipei, Taiwan, Apr. 2020. [Code]
• Yunsheng Bai*, Hao Ding*, Yizhou Sun, and Wei Wang, "Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching," Proc. of the 34rd AAAI Conference on Artificial Intelligence (AAAI '20), New York, New York, Feb. 2020. [GitHub]

2019

• Difan Zou*, Ziniu Hu*, Yewen Wang, Song Jiang, Yizhou Sun, and Quanquan Gu, "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks," Thirty-third Conf. on Neural Information Processing Systems (NeurIPS'19), Vancouver, Dec. 2019. [GitHub]
• Yu Zhou, Jianbin Huang, Heli Sun, Yizhou Sun, Shaojie Qiao, Stephen Wambura, "Recurrent meta-structure for robust similarity measure in heterogeneous information networks," ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 13, Issue 6, Dec. 2019.
• Rundong Li, Ningfang Mi, Mirek Riedewald, Yizhou Sun, and Yi Yao, "Abstract cost models for distributed data-intensive computations," Distributed and Parallel Databases, Volume 37, Issue 3, pp 411–439, Sept. 2019.
• Changjun Fan, Li Zeng, Yuhui Ding, Muhao Chen, Yizhou Sun and Zhong Liu, "Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network," Proc. 2019 ACM Int. Conf. on Information and Knowledge Management (CIKM’19), Beijing, China, Nov. 2019. [GitHub]
• Yang Yang, Yuhong Xu, Chunping Wang, Yizhou Sun, Fei Wu, Yueting Zhuang and Ming Gu, "Understanding Default Behavior in Peer-to-Peer Lending," Proc. 2019 ACM Int. Conf. on Information and Knowledge Management (CIKM’19), Beijing, China, Nov. 2019.
• Xiao Yang, Seungbae Kim and Yizhou Sun, "How Do Influencers Mention Brands in Social Media? Sponsorship Prediction of Instagram Posts," Proc. 2019 IEEE/ACM Int. Conf. on Advances in Social Networks Analysis and Mining (ASONAM'19), Vancouver, Canada, Aug. 2019.
• Yunsheng Bai, Hao Ding, Yang Qiao, Agustin Marinovic, Ken Gu, Ting Chen, Yizhou Sun, and Wei Wang, "Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity," Proc. of 2019 Int. Joint Conf. on Artificial Intelligence (IJCAI'19), Macao, China, Aug. 2019. [arXiv] [GitHub]
• Junheng Hao, Muhao Chen, Wenchao Yu, Yizhou Sun, and Wei Wang, "Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts," Proc. of 25th Int. ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'19) (Oral Presentation), Anchorage, AK, Aug. 2019.
• Ziniu Hu, Ting Chen, Kai-Wei Chang, and Yizhou Sun,"Few-Shot Representation Learning for Out-Of-Vocabulary Words," Proc. of 57th Annual Meeting of the Association for Computational Linguistics (ACL'19), Florence, Italy, July 2019. [GitHub]
• Xuelu Chen, Muhao Chen, Weijia Shi, Yizhou Sun, Carlo Zaniolo, "Embedding Uncertain Knowledge Graphs," Proc. of The 33rd AAAI Conference on Artificial Intelligence (AAAI '19), Honolulu, Hawaii, Jan. 2019. [GitHub]
• Zeyu Li, Jyun-Yu Jiang, Yizhou Sun and Wei Wang, "Personalized Question Routing via Heterogeneous Network Embedding," Proc. of The 33rd AAAI Conference on Artificial Intelligence (AAAI '19), Honolulu, Hawaii, Jan. 2019.
• Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, Wei Wang, "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation," Proc. 2019 ACM Int. Conf. on Web Search and Data Mining (WSDM'19), Melbourne, Australia, Feb. 2019. [GitHub]

2018

• Yunsheng Bai, Hao Ding, Yizhou Sun, Wei Wang, "Convolutional Set Matching for Graph Similarity," NIPS workshop on Relational Representation Learning, Montreal, Canada, Dec. 2018.
• Anahita Hosseini, Ting Chen, Wenjun Wu, Yizhou Sun, Majid Sarrafzadeh, "HeteroMed: Heterogeneous Information Network for Medical Diagnosis,"  Proc. of 2018 ACM Int. Conf. on Information and Knowledge Management (CIKM'18), Turin, Italy, Oct. 2018.
• Zhengxing Chen, Truong-Huy D Nguyen, Yuyu Xu, Christopher Amato, Seth Cooper, Yizhou Sun, Magy Seif El-Nasr, "The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games," Proc. of the 12th ACM Conf. on Recommender Systems (RecSys'18), Vancouver, British Columbia, Canada, Oct. 2018.
• Zhengxing Chen, Christopher Amato, Truong-Huy D. Nguyen, Seth Cooper, Yizhou Sun and Magy Seif El-Nasr, "Q-DeckRec: a Fast Deck Recommendation System for Collectible Card Games," Proc. of the IEEE Conf. on Computational Intelligence and Games (CIG'18), Maastricht University, The Netherlands, Aug. 2018.
• Ting Chen, Martin Renqiang Min, Yizhou Sun, "Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations," Proc. of the Thirty-fifth Int. Conf. on Machine Learning (ICML'18), Stockholm, Sweden, July. 2018. [Supplementary] [code](Oral)
• Yupeng Gu, Yizhou Sun, Yanen Li, Yang Yang, "RaRE: Social Rank Regulated Large-scale Network Embedding," Proc. of the 27th Int. Conf. on World Wide Web (WWW’18), Lyon, France, Apr. 2018. [slides] [code]

2017

• Rui Dong, Yizhou Sun, Lu Wang, Yupeng Gu, Yuan Zhong, "Weakly-Guided User Stance Prediction via Joint Modeling of Content and Social Interaction," Proc. of the 26th ACM Int. Conf. on Information and Knowledge Management (CIKM'17), Singapore, Nov. 2017.
• Chenguang Wang, Yangqiu Song, Haoran Li, Yizhou Sun, Ming Zhang, Jiawei Han, "Distant Meta-Path Similarities for Text-Based Heterogeneous Information Networks," Proc. of the 26th ACM Int. Conf. on Information and Knowledge Management (CIKM'17), Singapore, Nov. 2017.
• Ting Chen, Yizhou Sun, Yue Shi, Liangjie Hong, "On Sampling Strategies for Neural Network-based Collaborative Filtering," Proc. of 2017 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'17), Halifax, Nova Scotia, Canada, Aug. 2017. [Slides][code] [video]
• Yupeng Gu, Yizhou Sun, Jianxi Gao, "The Co-Evolution Model for Social Network Evolving and Opinion Migration," Proc. of 2017 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'17), Halifax, Nova Scotia, Canada, Aug. 2017. [Code] [video]
• He Jiang, Yangqiu Song, Chenguang Wang, Ming Zhang, and Yizhou Sun, "Semi-supervised Learning over Heterogeneous Information Networks by Ensemble of Meta-graph Guided RandomWalks," Proc. of 2017 Int. Joint Conf. on Artificial Intelligence (IJCAI'17), Melborne, Australia, Aug. 2017.
• Rundong Li, Ningfang Mi, Mirek Riedewald, Yizhou Sun, and Yi Yao, "A Case for Abstract Cost Models for Distributed Execution of Analytics Operators, Proc. of 19th Int. Conf. on Big Data Analytics and Knowledge Discovery (DaWak'17), Lyon, France, Aug. 2017.
• Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia Wasim Sadiq, Xiaofang Zhou, "ST-SAGE: A Spatial-Temporal Sparse Additive Generative Model for Spatial Item Recommendation," ACM TIST 8(3): 48:1-48:25, 2017.
• Yupeng Gu, Ting Chen, Yizhou Sun, Bingyu Wang, "Ideology Detection for Twitter Users with Heterogeneous Types of Links," Proc. of 2017 Int. Conf. on Social Computing, Behavioral-Cultural Modeling & Prediction (SBP'17), Washington D.C., USA, July, 2017. [arXiv Version]
• Yizhou Sun, Hongzhi Yin, Xiang Ren, "Recommendation in Context-Rich Environment: An Information Network Analysis Approach," (Conference Tutorial), Proc. of the 26th Int. Conf. on World Wide Web Companion (WWW'17), Perth, Australia, Apr. 2017.
• Zhengxing Chen, Su Xue, John Kolen, Navid Aghdaie, Kazi A Zaman, Yizhou Sun, Magy Seif El-Nasr, "EOMM: An Engagement Optimized Matchmaking Framework," Proc. of the 26th Int. Conf. on World Wide Web (WWW'17), Perth, Australia, Apr. 2017.
• Ting Chen and Yizhou Sun, "Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification," Proc. of 2017 ACM Int. Conf. on Web Search and Data Mining (WSDM'17), Cambridge UK, Feb. 2017. [arXiv Version] [Code]
• Chuan Shi, Yitong Li, Jiawei Zhang, Yizhou Sun, and Philip S. Yu, "A Survey of Heterogeneous Information Network Analysis," IEEE Trans. Knowl. Data Eng. 29(1): 17-37, 2017. (arXiv)

2016

• Zhengxing Chen, Yizhou Sun, Magy Seif El-Nasr, and Truong-Huy D. Nguyen, "Player Skill Decomposition in Multiplayer Online Battle Arenas," In Int. Academic Conf. on Meaningful Play (Meaningful Play 2016), East Lansing, MI, Oct. 2016.
• Yodsawalai Chodpathumwan, Amirhossein Aleyasen, Arash Termehchy, and Yizhou Sun, "Towards Representation Independent Similarity Search Over Graph Databases," Proc. of the 25th ACM Int. Conf. on Information and Knowledge Management (CIKM'16), Indianapolis, IN, Oct. 2016.
• Peng Xia, Shuangfei Zhai, Benyuan Liu, Yizhou Sun, Cindy X. Chen: "Design of reciprocal recommendation systems for online dating," Social Netw. Analys. Mining 6:32, 2016.
• Zhipeng Huang, Yudian Zheng, Reynold Cheng, Yizhou Sun, Nikos Mamoulis, and Xiang Li, "Meta Structure: Computing Relevance in Large Heterogeneous Information Networks," Proc. of 2016 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'16), San Francisco, CA, Aug. 2016.
• Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Kai Zhang, "Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events," Proc. 25th Int. Joint Conf. on Artifical Intelligence (IJCAI'16), New York City, USA, Jul. 2016.
• Xiaozhong Liu, Tian Xia, Yingying Yu, Chun Guo, Yizhou Sun, "Cross Social Media Recommendation," Proc. of the 10th Int. AAAI Conf. on Web and Social Media (ICWSM'16), Cologne, Germany, May 2016.
• Gang Fu, Ying Ding, Abhik Seal, Bin Chen, Yizhou Sun, and Evan Bolton, " Predicting drug target interactions using meta-path-based semantic network analysis," BMC Bioinformatics 17:160, 2016.
• Alex D. Wade, Kuansan Wang, Yizhou Sun, and Antonio Gulli, "WSDM Cup 2016: Entity Ranking Challenge," Proc. 2016 ACM Int. Conf. on Web Search and Data Mining (WSDM'16), San Francisco, California, USA, Feb. 2016.
• Yupeng Gu, Bo Zhao, David Hardtke, Yizhou Sun, "Learning Global Term Weights for Content-based Recommender Systems", Proc. of the 25th Int. Conf. on World Wide Web (WWW'16), Montreal, Canada, Apr. 2016.
• Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Haifeng Chen, and Guofei Jiang, "Integrating Community and Role Detection in Information Networks," in Proc of 2016 SIAM Int. Conf. on Data Mining (SDM'16), Miami, FL, May 2016.
• Chenguang Wang, Yizhou Sun, Yanglei Song, Jiawei Han, Yangqiu Song, Danli Wang, and Ming Zhang, "RelSim: Relation Similarity Search in Schema-Rich Heterogeneous Information Networks," in Proc of 2016 SIAM Int. Conf. on Data Mining (SDM'16), Miami, FL, May 2016.

2015

• Peng Xia, Benyuan Liu, Yizhou Sun, and Cindy X. Chen, "Reciprocal Recommendation System for Online Dating," Proc. of 2015 Int. Conf. on Advances in Social Network Analysis and Mining (ASONAM'15), Paris, France, Aug. 2015.
• Weiqing Wang, Hongzhi Yin, Ling Chen, Yizhou Sun, Shazia Wasim Sadiq, and Xiaofang Zhou, "Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation,"  Proc. of 2015 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'15), Sydney, Australia, Aug. 2015.
• Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, Juan-Zi Li, "Entity Matching across Heterogeneous Sources,"  Proc. of 2015 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'15), Sydney, Australia, Aug. 2015. [slides]
• Boliang Zhang, Hongzhao Huang, Xiaoman Pan, Sujian Li, Chin-Yew Lin, Heng Ji, Kevin Knight, Zhen Wen, Yizhou Sun, Jiawei Han, and Bulent Yener, "Context-aware Entity Morph Decoding," Proc. of 53rd Annual Meeting of the Association for Computational Linguistics (ACL'15), Beijing, China, Jul. 2015.
• Jiawei Han, Heng Ji, and Yizhou Sun, "Successful Data Mining Methods for NLP," Proc. of 53rd Annual Meeting of the Association for Computational Linguistics (ACL'15), Beijing, China, Jul. 2015. (Tutorial)
• Y. Chodpathumwan, A. Aleyasen, A. Termehchy, and Y. Sun, "Universal-DB: towards representation independent graph analytics," Proceedings of the VLDB Endowment 8 (12), 2016-2019, 2015. (Demo)
• Susan Collins, Yizhou Sun, Michal Kosinski, David Stillwell, Natasha Markuzon, "Are You Satisfied with Life?: Predicting Satisfaction with Life from Facebook," Proc. of 2015 Int. Conf. on Social Computing, Behavioral-Cultural Modeling, Prediction (SBP'15), Washington DC, Mar. 2015.
• Junxiang Chen, Wei Dai, Yizhou Sun, and Jennifer Dy, "Clustering and Ranking in Heterogeneous Information Networks via Gamma-Poisson Model," Proc. of the 2015 SIAM Int. Conf. on Data Mining (SDM'15), Vancouver, BC, Canada, Apr. 2015.
• Yang Yang, Jie Tang, Cane Wing-Ki Leung, Yizhou Sun, Qicong Chen, Juanzi Li, and Qiang Yang, "RAIN: Social Role-Aware Information Diffusion," Proc. of the 29th AAAI Conf. on Artificial Intelligence (AAAI'15), Austin, Texas, USA, Jan 2015.

2014

• Huan Gui, Yizhou Sun, Jiawei Han, and George Brova, "Modeling Topic Diffusion in Multi-Relational Bibliographic Information Networks", Proc. of 2014 ACM Int. Conf. on Information and Knowledge Management (CIKM'14), Shanghai, China, Nov. 2014.
• Xiaozhong Liu, Yingying Yu, Chun Guo, and Yizhou Sun, “Meta-Path-Based Ranking with Pseudo Relevance Feedback on Heterogeneous Graph for Citation Recommendation,” Proc. of 2014 ACM Int. Conf. on Information and Knowledge Management (CIKM’14), Shanghai, China, Nov. 2014.
• Xiaozhong Liu, Yingying Yu, Chun Guo, Yizhou Sun, and Liangcai Gao, “Full-Text based Context-Rich Heterogeneous Network Mining Approach for Citation Recommendation,” ACM/IEEE Joint Conference on Digital Libraries (JCDL’14), London, 2014.
• Yupeng Gu, Yizhou Sun, Ning Jiang, Bingyu Wang, Ting Chen, "Topic-Factorized Ideal Point Estimation Model for Legislative Voting Network," Proc. of 2014 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’14), New York, NY, Aug. 2014. [slides] [demo][code and dataset]
• Xiaozhong Liu, Liangcai Gao, Noriko Hara, and Yizhou Sun. "Open educational resource based information understanding via pdf document interaction," (poster), Proc. of the 2014 ACM Conf. on Web Science (WebSci’14), pages 291–292, Bloomington, Indiana, USA, 2014.
• Boliang Zhang, Hongzhao Huang, Xiaoman Pan, Heng Ji, Kevin Knight, Zhen Wen, Yizhou Sun, Jiawei Han and Bulent Yener, "Be Appropriate and Funny: Automatic Entity Morph Encoding", Proc. of 2014 Annual Meeting of the Association for Computational Linguistics (ACL'14), Baltimore, USA, June 2014.
• Y. Chodpathumwan, A. Termehchy, Yizhou Sun, A. Aleyasin, and J. Picado, "Toward Representation Independent Similarity Search Over Graphs," ACM Proceedings of Workshop on GRAph Data management Experiences and Systems (GRADES 2014), Snowbird, Utah, June 2014.
• Fangbo Tao, Jiawei Han, Heng Ji, George Brova,Chi Wang, Ahmed El-Kishky, Jialu Liu, Xiang Ren, Yizhou Sun, "NewsNetExplorer: Automatic Construction and Exploration of News Information Networks", (system demo), Proc. of 2014 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'14), Snowbird, UT, June 2014.
• Xiao Yu, Xiang Ren, Yizhou Sun, Quanquan Gu, Bradley Sturt, Urvashi Khandelwal, Brandon Norick, and Jiawei Han, "Personalized Entity Recommendation: A Heterogeneous Information Network Approach", Proc. 2014 ACM Int. Conf. on Web Search and Data Mining (WSDM'14), New York City, NY, Feb. 2014.

2013

• Hyungsul Kim, Xiang Ren, Yizhou Sun, Chi Wang, and Jiawei Han, "Semantic Frame-Based Document Representation for Comparable Corpora", Proc. 2013 IEEE Int. Conf.on Data Mining (ICDM'13), Dallas, TX, Dec. 2013.
• Xiao Yu, Xiang Ren, Yizhou Sun, Bradley Sturt, Urvashi Khandelwal, Quanquan Gu, Brandon Norick, and Jiawei Han, "HeteRec: Entity Recommendation in Heterogeneous Information Networks with Implicit User Feedback", Proc. of 2013 ACM Int. Conf. Series on Recommendation Systems (RecSys'13), Hong Kong, Oct. 2013.
• Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan, Philip S. Yu, and Xiao Yu, "PathSelClus: Integrating Meta-Path Selection with User-Guided Object Clustering in Heterogeneous Information Networks," ACM Transactions on Knowledge Discovery from Data (TKDD), 7(3):11:1-11:23, Sep. 2013.
• Yizhou Sun and Jiawei Han, "Meta-path-based search and mining in heterogeneous information networks," IEEE Tsinghua Science and Technology, 18(4): 329-338, Aug. 2013. (Best Paper Award)
• Yizhou Sun, Jie Tang, Jiawei Han, Cheng Chen, and Manish Gupta, "Co-Evolution of Multi-Typed Objects in Dynamic Heterogeneous Information Networks", accepted by IEEE Trans. on Knowledge and Data Engineering (TKDE), June 2013.
• Hongzhi Yin, Yizhou Sun, Bin Cui, Zhiting Hu, and Ling Chen, "LCARS: A Local-Content-Aware Recommender System," Proc. of 2013 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’13), Chicago, IL, Aug. 2013.
• Hongzhao Huang, Zhen Wen, Dian Yu, Heng Ji, Yizhou Sun, Jiawei Han and He Li, "Resolving Entity Morphs in Censored Data", Proc. of 2013 Annual Meeting of the Association for Computational Linguistics (ACL'13), Sofia, Bulgaria, Aug. 2013.
• Xiao Yu, Xiang Ren, Quanquan Gu, Yizhou Sun, and Jiawei Han, "Collaborative Filtering with Entity Similarity Regularization in Heterogeneous Information Networks", Proc. of IJCAI-13 HINA workshop (IJCAI-HINA'13), Beijing, China, Aug. 2013.
• Fangbo Tao, Xiao Yu, Kin Hou Lei, George Brova, Xiao Cheng Jiawei Han, Rucha Kanade, Yizhou Sun, Chi Wang, Lidan Wang, Tim Weninger, "Research-Insight: Providing Insight on Research by Publication Network Analysis", (system demo), Proc. of 2013 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'13), New York, NY, June 2013.
• Jing Gao, Feng Liang, Wei Fan, Yizhou Sun, and Jiawei Han, "A Graph-based Consensus Maximization Approach for Combining Multiple Supervised and Unsupervised Models", IEEE Transactions on Knowledge and Data Engineering (TKDE), 25(1):15-28, 2013.

2012

• Yizhou Sun and Jiawei Han, ``Mining Heterogeneous Information Networks: A Structural Analysis Approach", SIGKDD Explorations, 14(2):20-28, 2012.
• Hyungsul Kim, Yizhou Sun, Julia Hockenmaier, and Jiawei Han, "ETM: Entity Topic Models for Mining Documents Associated with Entities", Proc. of 2012 IEEE Int. Conf. on Data Mining (ICDM'12), Brussels, Belgium, Dec. 2012 (selected as one of the best papers )

• Yang Yang, Nitesh Chawla, Yizhou Sun, and Jiawei Han, "Predicting Links in Multi-Relational and Heterogeneous Networks", Proc. of 2012 IEEE Int. Conf. on Data Mining (ICDM'12), Brussels, Belgium, Dec. 2012.

• Xiao Yu, Yizhou Sun, Brandon Norick, Tiancheng Mao, and Jiawei Han, "User Guided Entity Similarity Search Using Meta-Path Selection in Heterogeneous Information Networks", Proc. of 2012 Int. Conf. on Information and Knowledge Management (CIKM'12), Maui, Hawaii, Oct. 2012.

• Manish Gupta, Jing Gao, Yizhou Sun, and Jiawei Han, "Community Trend Outlier Detection Using Soft Temporal Pattern Mining", Proc. of 2012 European Conf. on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD'12), Bristol, UK, Sept. 2012. [pdf]

• Yizhou Sun, Jiawei Han, Xifeng Yan, and Philip S. Yu, "Mining Knowledge from Interconnected Data: A Heterogeneous Information Network Analysis Approach", Proc. 2012 Int. Conf. on Very Large Data Bases (VLDB'12/PVLDB), Istanbul, Turkey, Aug. 2012. (conference tutorial) [pdf]

• Xiao Yu, Yizhou Sun, Peixiang Zhao, Jiawei Han, "Query-Driven Discovery of Semantically Similar Substructures in Heterogeneous Networks", Proc. of 2012 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, Aug. 2012. (System Demo) [pdf]

• Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan, Philip S. Yu, and Xiao Yu, "Integrating Meta-Path Selection with User-Guided Object Clustering in Heterogeneous Information Networks", Proc. 2012 ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, Aug. 2012. (Best Student Paper Award) [pdf][slides]

• Manish Gupta, Jing Gao, Yizhou Sun, and Jiawei Han, "Integrating Community Matching and Outlier Detection for Mining Evolutionary Community Outliers", Proc. 2012 ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, Aug. 2012. [pdf]

• Yizhou Sun, Charu C. Aggarwal, and Jiawei Han, "Relation Strength-Aware Clustering of Heterogeneous Information Networks with Incomplete Attributes", PVLDB 5(5):394-405, 2012. (Also, Proc. 2012 Int. Conf. on Very Large Data Bases (VLDB'12/PVLDB), Istanbul, Turkey, Aug. 2012.) [pdf]

• Jiawei Han, Yizhou Sun, Xifeng Yan, and Philip S. Yu, "Mining Knowledge from Data: An Information Network Analysis Approach", Proc. 2012 IEEE Int. Conf. on Data Engineering (ICDE'12), Arlington, VA, Apr. 2012. (Conference tutorial, 5 pages) [pdf]
• Lu-An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Wen-Chih Peng, Yizhou Sun, Alice Leung, and Thomas La Porta, "Multidimensional Sensor Data Analysi in Cyber-Physical System: An Atypical Approach," International Journal of Distributed Sensor Networks, Volume 2012.
• Yizhou Sun, Jiawei Han, Charu C. Aggarwal, and Nitesh V. Chawla, "When Will It Happen? --- Relationship Prediction in Heterogeneous Information Networks", Proc. 2012 ACM Int. Conf. on Web Search and Data Mining (WSDM'12), Seattle, WA, Feb. 2012. (Acceptance rate: 75/362 = 20.7%) [pdf]

• Lu-An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Wen-Chih Peng, Yizhou Sun, Hector Gonzalez, and Sebastian Seith, "Multidimensional Analysis of Atypical Events in Cyber-Physical Data", Proc. 2012 IEEE Int. Conf. on Data Engineering (ICDE'12), Arlington, VA, Apr. 2012. (Acceptance rate approx. 20%) [pdf]

2011

• Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S. Yu, and Tianyi Wu, "PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks", PVLDB 4(11): 992-1003, 2011. (Also, Proc. of 2011 Int. Conf. on Very Large Data Bases (VLDB'11/PVLDB), Seattle, WA, Aug. 2011.) (Acceptance rate: 100/553 = 18.1%) [pdf] [slides][DBIS data] (VLDB 2022 Test of Time Award)

• Yang Yang, Yizhou Sun, Saurav Pandit, Nitesh Chawla and Jiawei Han, "Is Objective Function the Silver Bullet? A Case Study of Community Detection Algorithms on Social Networks", Proc. of 2011 Int. Conf. on Advances in Social Network Analysis and Mining (ASONAM'11), Kaohsiung, Taiwan, July 2011. (Short paper, acceptance rate: unknown) [pdf]

• Yizhou Sun, Rick Barber, Manish Gupta, Charu C. Aggarwal and Jiawei Han, "Co-Author Relationship Prediction in Heterogeneous Bibliographic Networks", Proc. of 2011 Int. Conf. on Advances in Social Network Analysis and Mining (ASONAM'11), Kaohsiung, Taiwan, July 2011. (Acceptance rate: 25%) [pdf] [slides][errata]

• Manish Gupta, Charu Aggarwal, Jiawei Han and Yizhou Sun, "Evolutionary Clustering and Analysis of Bibliographic Networks", Proc. of 2011 Int. Conf. on Advances in Social Network Analysis and Mining (ASONAM'11), Kaohsiung, Taiwan, July 2011. (Best Paper Award, acceptance rate: 25%) [pdf]

• Tim Weninger, Marina Danilevsky, Fabio Fumarola, Joshua Hailpern, Jiawei Han, Ming Ji, Thomas J. Johnston, Surya Kallumadi, Hyungsul Kim, Zhijin Li, David McCloskey, Yizhou Sun, Nathan E. TeGrotenhuis, Chi Wang, and Xiao Yu, "WinaCS: Construction and Analysis of Web-Based Computer Science Information Networks", Proc. 2011 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'2011). (System demo paper, acceptance rate approx. 35%) [pdf]

• Hieu Khac Le, J. Pasternack, Hossein Ahmadi, Manish Gupta, Yizhou Sun, Tarek Abdelzaher, Jiawei Han, Dan Roth, Boleslaw K. Szymanski, S. Adali, "Apollo: Towards Factfinding in Participatory Sensing", Proc. ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN'11), Apr. 2011. (System demo paper, acceptance rate: unkown)

• Manish Gupta, Yizhou Sun, and Jiawei Han, "Trust Analysis with Clustering", Proc. of 2011 Int. WorldWide Web Conf. (WWW'11), Hyderabad, India, March 2011. (Poster paper, acceptance rate: 62/202 = 30.7%) [pdf]

2010

• Jianbin Huang, Heli Sun, Jiawei Han, Hongbo Deng, Yizhou Sun, Yaguang Liu, "SHRINK: A Structural Clustering Algorithm for Detecting Hierarchical Communities in Networks", Proc. 2010 ACM Int. Conf. on Information and Knowledge Management (CIKM'10), Toronto, Canada, Oct. 2010, pp. 219-228. (Acceptance rate: 127/945 = 13.4%) [pdf]

• Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han, Jing Gao, "Graph Regularized Transductive Classification on Heterogeneous Information Networks", Proc. 2010 European Conf. on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'10), Barcelona, Spain, Sept. 2010. (Acceptance rate: 120/658 = 18.24%) [pdf]

• Jing Gao, Feng Liang, Wei Fan, Chi Wang, Yizhou Sun, Jiawei Han, "On Community Outliers and Their Efficient Detection in Information Networks", Proc. 2010 ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'10), Washington, D.C., July 2010. (Acceptance rate: 13.3%) [pdf]

• Yizhou Sun, Jie Tang, Jiawei Han, Manish Gupta, and Bo Zhao, "Community Evolution Detection in Dynamic Heterogeneous Information Networks", Proc. 2010 KDD Workshop on Mining and Learning with Graphs (MLG'10), Washington, D.C., July 2010. (Workshop paper) [pdf]

• Jiawei Han, Yizhou Sun, Xifeng Yan, and Philip S. Yu, "Mining Knowledge from Databases: An Information Network Analysis Approach", Proc. 2010 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'10), Indianapolis, IN, June 2010. (Conference tutorial) [pdf] [slides]

• Cuiping Li, Jiawei Han, Xin Jin, Yizhou Sun, Yintao Yu, and Tianyi Wu, "Fast Computation of SimRank for Static and Dynamic Information Networks", Proc. 2010 Int. Conf. on Extending Data Base Technology (EDBT'10), Lausanne, Switzerland, March 2010. (Acceptance rate: 54/307 = 18%) [pdf]

• Tianyi Wu, Yizhou Sun, Cuiping Li, and Jiawei Han, "Region-based Online Promotion Analysis", Proc. 2010 Int. Conf. on Extending Data Base Technology (EDBT'10), Lausanne, Switzerland, March 2010. (Acceptance rate:  54/307 = 18%) [pdf]

2009

• Yizhou Sun, Jiawei Han, Jing Gao, and Yintao Yu, "iTopicModel: Information Network-Integrated Topic Modeling", Proc. 2009 Int. Conf. on Data Mining (ICDM'09), Miami, FL, Dec. 2009. (Full paper, acceptance rate: 70/786 = 8.9%) [pdf] [slides] [DBLP_Data] [Cora_Data]

• Jing Gao, Feng Liang, Wei Fan, Yizhou Sun, and Jiawei Han, "Bipartite Graph-based Consensus Maximization among Supervised and Unsupervised Models", Proc. NIPS 2009 Neural Info. Processing Systems Conf. (NIPS'09), Vancouver, B.C., Canada, Dec. 2009. (Acceptance rate: 263/1105 = 23.8%) [pdf]

• Peixiang Zhao, Jiawei Han, Yizhou Sun, "P-Rank: A Comprehensive Structural Similarity Measure over Information Networks", Proc. 2009 ACM Conf. on Information and Knowledge Management (CIKM'09), Hong Kong, China, Nov. 2009. (Acceptance rate: 123/847 = 14.5%) [pdf]

• Yintao Yu, Cindy X. Lin, Yizhou Sun, Chen Chen, Jiawei Han, Binbin Liao, Tianyi Wu, ChengXiang Zhai, Duo Zhang, and Bo Zhao, "iNextCube: Information Network-Enhanced Text Cube", Proc. 2009 Int. Conf. on Very Large Data Bases  (VLDB'09), Lyon, France, Aug. 2009. (System demo paper, acceptance rate: 29/107 = 27.1%) [pdf]

• Yizhou Sun, Yintao Yu, and Jiawei Han, "Ranking-Based Clustering of Heterogeneous Information Networks with Star Network Schema", Proc. 2009 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'09), Paris, France, June 2009. (Full presentation, acceptance rate: 51/538 = 9.5%) [pdf] [slides] [data] [video]

• Jing Gao, Wei Fan, Yizhou Sun, and Jiawei Han, "Heterogeneous Source Consensus Learning via Decision Propagation and Negotiation", Proc. 2009 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'09), Paris, France, June 2009. (Short presentation, acceptance rate: (51+61)/538 = 20.8%) [pdf]

• Yizhou Sun, Jiawei Han, Peixiang Zhao, Zhijun Yin, Hong Cheng, and Tianyi Wu, "RankClus: Integrating Clustering with Ranking for Heterogeneous Information Network Analysis", Proc. 2009 Int. Conf. on Extending Data Base Technology (EDBT'09), Saint-Petersburg, Russia, Mar. 2009. (Acceptance rate: 92/283 = 32.5%) [pdf] [slides] [network generator]
• This work has also been selected as poster for "The Third Annual DHS (Department of Homeland Security) University Network Summit", Washington, D.C., U.S., Mar. 2009.

2008

• Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, and Yizhou Sun, "Sampling Cube: A Framework for Statistical OLAP over Sampling Data", Proc. 2008 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'08), Vancouver, BC, Canada, June 2008. (Acceptance rate: 78/435 = 17.9%) [pdf]

• Yizhou Sun, Tianyi Wu, Zhijun Yin, Hong Cheng, Jiawei Han, Xiaoxin Yin, and Peixiang Zhao, "BibNetMiner: Mining Bibliographic Information Networks", Proc. 2008 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'08), Vancouver, BC, Canada, June 2008. (System demo paper, acceptance rate: 30/94 = 31.9%) [pdf]

• Shan He, Cheng Hu, Guojie Song, Kunqing Xie, Yizhou Sun, "Real-Time Short-Term Traffic Flow Forecasting Based on Process Neural Network", Proc. 5th Int. Symp. on Neural Networks (ISNN'08), Beijing, China, Sept.2008. (Acceptance rate: 192/522 = 36.7%)

2007

• Yizhou Sun, Kunqing Xie, Ning Liu, Shuicheng Yan, Benyu Zhang, and Zheng Chen, "Causal Relation of Queries from Temporal Logs", Proc. 16th Int. Conf. on World Wide Web (WWW'07), Banff, Alberta, Canada, May 2007. (Poster paper) [pdf]