Kai Han

Some selected publications of mine are listed below. First authors, who are graduate students independently supervised by me, are indicated with a superscript ^. Corresponding authors are denoted by an asterisk *. Additional publications of mine can be found in my DBLP entry:https://dblp.org/pid/51/4757-3.html .

• [AAAI] Shuang Cui^, Kai Han*, He Huang: Deletion-Robust Submodular Maximization with Knapsack Constraints. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024.
• [NeurIPS] Kai Han*, You Wu, He Huang, Shuang Cui: Triple Eagle: Simple, Fast and Practical Budget-Feasible Mechanisms. Advances in Neural Information Processing Systems (NeurIPS), 2023.
• [TOIS] Zhizhuo Yin^, Kai Han*, Pengzi Wang, Xi Zhu: H3GNN: Hybrid Hierarchical HyperGraph Neural Network for Personalized Session-based Recommendation. ACM Transactions on Information Systems . Early access: https://doi.org/10.1145/3630002.
• [WWW] He Huang, Kai Han*, Shuang Cui, Jing Tang. Randomized Pricing with Deferred Acceptance for Revenue Maximization with Submodular Objectives. Proceedings of the Web Conference (WWW), pages 3530–3540, 2023.
• [WWW] Shuang Cui^, Kai Han*, Jing Tang, He Huang*. Constrained Subset Selection from Data Streams for Profit Maximization. Proceedings of the Web Conference (WWW), pages 1822–1831, 2023.
• [AAAI] Shuang Cui^, Kai Han*, Jing Tang, He Huang*, Xueying Li, Zhiyu Li. Practical Parallel Algorithms for Submodular Maximization subject to a Knapsack Constraint with Nearly Optimal Adaptivity. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages 7261–7269, 2023.
• [SIGMETRICS] Shuang Cui^, Kai Han*, Jing Tang, He Huang*, Xueying Li, Zhiyu Li. Streaming Algorithms for Constrained Submodular Maximization. Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (ACM SIGMETRICS), pages 65–66, 2023. Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS)), 6(3):54:1–54:32, 2022.
• [IPM] Benwei Wu^, Kai Han*, Enpei Zhang.On the task assignment with group fairness for spatial crowdsourcing. Information Processing & Management , 60(2):103175, 2023. (SCI IF: 8.6)
• [TKDE] Zhizhuo Yin^, Kai Han*, Pengzi Wang, and Haibing Hu. Multi Global Information Assisted Streaming Session-Based Recommendation System. IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(8): 8245-8256, 2023.
• [NeurIPS] Qing Xiu^, Kai Han*, Jing Tang, Shuang Cui, He Huang*. Chromatic Correlation Clustering, Revisited. Advances in Neural Information Processing Systems (NeurIPS), pages 26147–26159, 2022.
• [KDD] Qianhao Cong, Jing Tang*, Kai Han, Yuming Huang, Lei Chen, Yeow Meng Chee: Noisy Interactive Graph Search, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (ACM KDD), pages 231–240, 2022.
• [ICDE] Jing Tang, Yuqing Zhu, Xueyan Tang, Kai Han: Distributed Influence Maximization for Large-Scale Online Social Networks, Proceedings of the IEEE International Conference on Data Engineering (IEEE ICDE), pages 1152–1165, 2022.
• [SIGMOD] Kai Han*, Benwei Wu, Jing Tang, Shuang Cui, Çigdem Aslay, Laks V. S. Lakshmanan: Efficient and Effective Algorithms for Revenue Maximization in Social Advertising. Proceedings of the ACM SIGMOD International Conference on Management of Data (ACM SIGMOD), pages 671-684, 2021.
• [ICML] Shuang Cui^, Kai Han*, Tianshuai Zhu, Jing Tang, Benwei Wu, He Huang: Randomized Algorithms for Submodular Function Maximization with a k-System Constraint. Proceedings of the International Conference on Machine Learning (ICML), pages 2222-2232, 2021.
• [SIGMETRICS] Kai Han*, Shuang Cui, Tianshuai Zhu, Enpei Zhang, Benwei Wu, Zhizhuo Yin, Tong Xu, Shaojie Tang, He Huang., Approximation Algorithms for Submodular Data Summarization with a Knapsack Constraint, Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (ACM SIGMETRICS), pages 65–66, 2021. Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 5(1): 05:1-05:31 (2021). [Acceptance Rate: 12.1% (38 out of 315)]
• [SIGMETRICS] Jing Tang, Xueyan Tang, Andrew Lim, Kai Han, Chongshou Li, and Junsong Yuan，Revisiting Modified Greedy Algorithm for Monotone Submodular Maximization with a Knapsack Constraint. Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (ACM SIGMETRICS), pages 63–64, 2021. Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 5(1):08:1–08:22, 2021. [Acceptance Rate: 12.1% (38 out of 315)]
• [VLDBJ] Keke Huang, Jing Tang, Kai Han, Xiaokui Xiao, Wei Chen, Aixin Sun, Xueyan Tang, and Andrew Lim. Efficient Approximation Algorithms for Adaptive Influence Maximization. The International Journal on Very Large Data Bases , 29(6):1385-1406, 2020.
• [NeurIPS] Kai Han*, Zongmai Cao, Shuang Cui, Benwei Wu: Deterministic Approximation for Submodular Maximization over a Matroid in Nearly Linear Time. Neural Information Processing Systems (NeurIPS), pages 430–441, 2020.
• [IJOC] Kai Han*, Yuntian He, Alex. Liu, Shaojie Tang, He Huang. Differentially Private and Budget Limited Bandit Learning over Matroids. INFORMS Journal on Computing, 32(3): 790-804，2020. （UTD-24 Journal）
• [TKDE] Kai Han*, Yuntian He, Keke Huang, Xiaokui Xiao, Shaojie Tang, Jingxin Xu, Liusheng Huang, “Best Bang for the Buck: Cost-Effective Seed Selection for Online Social Networks”. IEEE Transactions on Knowledge and Data Engineering, 32(12): 2297-2309, 2020.
• [VLDB] Kai Han*, Fei Gui, Xiaokui Xiao, Jing Tang, Yuntian He, Zongmai Cao, He Huang. Efficient and Effective Algorithms for clustering Uncertain Graphs. Proceedings of the VLDB Endowment, 12(6): 667-680, 2019.
• [INFOCOM] Haisheng Tan; Shaofeng H.-C. Jiang; Zhenhua Han, Liuyan Liu, Kai Han, Qinglin Zhao, Camul: Online Caching on Multiple Caches with Relaying and Bypassing. Proceedings of the IEEE International Conference on Computer Communications (IEEE INFOCOM) pages 244-252, 2019.
• [IOTJ] Yu-E Sun, He Huang, Shigang Chen, You Zhou, Kai Han, Wenjian Yang: Privacy-preserving estimation of k-Persistent Traffic in Vehicular Cyber-Physical Systems, IEEE Internet of Things Journal, 6(5): 8296-8309, 2019 (SCI IF: 10.6)
• [TMC] Kai Han*, Huan Liu, Shaojie Tang, and Mingjun Xiao, Jun Luo: Differentially Private Mechanisms for Budget Limited Mobile Crowdsourcing, IEEE Transactions on Mobile Computing, 18(4): 934-946, 2019.
• [TON] Kai Han*, He Huang, Jun Luo: Quality-Aware Pricing for Mobile Crowdsensing, IEEE/ACM Transactions on Networking, 26(4): 1728-1741, 2018.
• [TMC] Yu-e Sun, He Huang, Shigang Chen, Hongli Xu, Kai Han, Yian Zhou: Persistent Traffic Measurement Through Vehicle-to-Infrastructure Communications in Cyber-Physical Road Systems, IEEE Transactions on Mobile Computing, 18(7): 1616-1630, 2019.
• [TKDE] Kai Han*, Yuntian He, Xiaokui Xiao, Shaojie Tang, Fei Gui, Chaoting Xu, Jun Luo, Organizing an Influential Social Event under a Budget Constraint, IEEE Transactions on Knowledge and Data Engineering, 31(12): 2379-2392, 2019.
• [VLDB] Kai Han*, Keke Huang#, Xiaokui Xiao#, Jing Tang, Aixin Sun, Xueyan Tang: Efficient Algorithms for Adaptive Influence Maximization, Proceedings of the VLDB Endowment 11(9): 1029-1040, 2018.
• [INFOCOM] He Huang, Yu-e Sun, Shigang Chen, Shaojie Tang, Kai Han, Jing Yuan, Wenjian Yang: You Can Drop but You Can't Hide: K-persistent Spread Estimation in High-speed Networks. Proceedings of the IEEE International Conference on Computer Communications (IEEE INFOCOM) pages 1889-1897, 2018.
• [MobiHoc] Kai Han*, Chaoting Xu, Fei Gui, Shaojie Tang, He Huang, Jun Luo: Discount Allocation for Revenue Maximization in Online Social Networks. Proceedings of the International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc) pages 121-130, 2018.
• [ICDE] Kai Han*, Yuntian He,Xiaokui Xiao, Shaojie Tang, Fei Gui, Chaoting Xu,Jun Luo: Budget-Constrained Organization of Influential Social Events, Proceedings of the IEEE International Conference on Data Engineering (IEEE ICDE) pages 917-928, 2018.
• [MobiHoc] Kai Han*, Yuntian He, Haisheng Tan, Shaojie Tang, He Huang, Jun Luo: Online Pricing for Mobile Crowdsourcing with Multi-Minded Users. Proceedings of the International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc), pages 18:1-18:10, 2017
• [TPDS] Guoju Gao, Mingjun Xiao, Jie Wu, Kai Han, Liusheng Huang, Zhenhua Zhao: Opportunistic Mobile Data Offloading with Deadline Constraints. IEEE Transactions on Parallel and Distributed Systems, 28(12): 3584-3599, 2017
• [ICDCS] Shaojie Tang, Yaqin Zhou, Kai Han, Zhao Zhang, Jing Yuan, Weili Wu: Networked Stochastic Multi-armed Bandits with Combinatorial Strategies. Proceedings of the IEEE International Conference on Distributed Computing Systems (IEEE ICDCS), pages 786-793, 2017
• [MobiHoc] Kai Han*, He Huang, Jun Luo: Posted pricing for robust crowdsensing. Proceedings of the International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc), pages 261-270, 2016.
• [TC] Kai Han*, C. Zhang, J. Luo, M. Hu and B. Veeravalli: Truthful Scheduling Mechanisms for Powering Mobile Crowdsensing, IEEE Transactions on Computers, 65(1): 294-307, 2016.
• [SECON] Guoju Gao, Mingjun Xiao, Jie Wu, Kai Han, Liusheng Huang: Deadline-Sensitive Mobile Data Offloading via Opportunistic Communications. Proceedings of the Annual IEEE International Conference on Sensing, Communication, and Networking (IEEE SECON), pages 1-9, 2016.
• [TON] Kai Han*, C. Zhang, and J. Luo: Taming the Uncertainty: Budget Limited Robust Crowdsensing through Online Learning, IEEE/ACM Transactions on Networking, 24(3): 1462-1475, 2016.
• [TON] Kai Han*, Jun Luo, Xiang Liu, Mingjun Xiao, and Liusheng Huang: Achieving Energy Efficiency and Reliability for Data Dissemination in Duty-Cycled WSNs, IEEE/ACM Transactions on Networking, 23(4), 1041-1052, 2015.
• [INFOCOM] Kai Han*, Z. Hu, J. Luo, and L. Xiang, “RUSH: RoUting and Scheduling for Hybrid Data Center Networks,” Proceedings of the IEEE International Conference on Computer Communications (IEEE INFOCOM), pages 415-423, 2015.
• [TON] Kai Han*, Yang Liu, and Jun Luo, "Duty-Cycle-Aware Minimum-Energy Multicasting in Wireless Sensor Networks," IEEE/ACM Transactions on Networking, 21(3): 910-923, 2013.
• [COMMAG] Kai Han*, Jun Luo, Yang Liu, and A. Vasilakos, "Algorithm Design for Data Communications in Duty-Cycled Wireless Sensor Networks: A Survey," IEEE Communications Magazine, 51(7): 107-113, 2013. (ESI，SCI IF: 11.2, Google Scholar Citations 220+)
• [TVT] Kai Han*, Liu Xiang, Jun Luo, and Yang Liu, "MEGCOM: Minimum-Energy Group COMmunication in Multi-hop Wireless Networks," IEEE Transactions on Vehicular Technology, 63(4): 1790-1801, 2014.
• [SECON] Kai Han*, Chi Zhang, and Jun Luo: BLISS: Budget LImited robuSt crowdSensing through Online Learning, Proceedings of the Annual IEEE International Conference on Sensing, Communication, and Networking (IEEE SECON), pages 555-563, 2014.
• [MohiHoc] Kai Han*, Liu Xiang, Jun Luo, Ming-jun Xiao, and Liusheng Huang: Energy-Efficient Reliable Data Dissemination in Duty-Cycled Wireless Sensor Networks, Proceedings of the International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc), pages 287-292, 2013.
• [MobiHoc] Kai Han*, Liu Xiang, Jun Luo, and Yang Liu: Minimum-Energy Connected Coverage in Wireless Sensor Networks with Omni-Directional and Directional Features, Proceedings of the International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc) , pages 85-94, 2012.

• TPC Members for: ICML/NeurIPS/WWW/KDD/AAAI/WSDM/ICDCS/ICNP.