| Differentially private generative adversarial network L Xie, K Lin, S Wang, F Wang, J Zhou arXiv preprint arXiv:1802.06739, 2018 | 438 | 2018 |
| Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning K Lin, R Zhao, Z Xu, J Zhou Proceedings of the 24th ACM SIGKDD International Conference on Knowledge, 2018 | 379 | 2018 |
| Transfer Learning in Deep Reinforcement Learning: A Survey Z Zhu, K Lin, J Zhou arXiv preprint arXiv:2009.07888, 2020 | 273 | 2020 |
| Privacy-preserving distributed multi-task learning with asynchronous updates L Xie, IM Baytas, K Lin, J Zhou Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 51 | 2017 |
| Off-policy imitation learning from observations Z Zhu, K Lin, B Dai, J Zhou Advances in Neural Information Processing Systems 33, 12402-12413, 2020 | 47 | 2020 |
| Powernet: Multi-agent deep reinforcement learning for scalable powergrid control D Chen, K Chen, Z Li, T Chu, R Yao, F Qiu, K Lin IEEE Transactions on Power Systems 37 (2), 1007-1017, 2021 | 39 | 2021 |
| A Unified Linear Speedup Analysis of Stochastic FedAvg and Nesterov Accelerated FedAvg Z Qu, K Lin, Z Li, J Zhou, Z Zhou arXiv preprint arXiv:2007.05690, 2020 | 34* | 2020 |
| Multi-Task Feature Interaction Learning K Lin, J Xu, IM Baytas, S Ji, J Zhou Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 33 | 2016 |
| DialFRED: Dialogue-Enabled Agents for Embodied Instruction Following X Gao, Q Gao, R Gong, K Lin, G Thattai, GS Sukhatme IEEE Robotics Autom. Lett., 2022 | 25 | 2022 |
| Collaborative deep reinforcement learning K Lin, S Wang, J Zhou arXiv preprint arXiv:1702.05796, 2017 | 25 | 2017 |
| Phenotree: Interactive visual analytics for hierarchical phenotyping from large-scale electronic health records IM Baytas, K Lin, F Wang, AK Jain, J Zhou IEEE Transactions on Multimedia 18 (11), 2257-2270, 2016 | 21 | 2016 |
| Synergies that Matter: Efficient Interaction Selection via Sparse Factorization Machine J Xu, K Lin, PN Tan, J Zhou 2016 SIAM International Conference on Data Mining (SDM16), 108-116, 2016 | 14 | 2016 |
| Ranking Policy Gradient K Lin, J Zhou ICLR 2020, 2019 | 12 | 2019 |
| Interactive Multi-Task Relationship Learning K Lin, J Zhou 2016 IEEE 16th International Conference on Data Mining (ICDM), 2016 | 12 | 2016 |
| RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection. B Liu, D Wang, K Lin, PN Tan, J Zhou IJCAI, 1505-1511, 2021 | 9 | 2021 |
| Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations Z Zhu, K Lin, B Dai, J Zhou arXiv preprint arXiv:2004.00530, 2020 | 9 | 2020 |
| Learning to Act with Affordance-Aware Multimodal Neural SLAM Z Jia, K Lin, Y Zhao, Q Gao, G Thattai, G Sukhatme IROS 2022, 2022 | 8 | 2022 |
| LUMINOUS: Indoor Scene Generation for Embodied AI Challenges Y Zhao, K Lin, Z Jia, Q Gao, G Thattai, J Thomason, GS Sukhatme NeurIPS 2021 (CtrlGen Workshop), 2021 | 8 | 2021 |
| Efficient Collaborative Multi-Agent Deep Reinforcement Learning for Large-Scale Fleet Management K Lin, R Zhao, Z Xu, J Zhou arXiv preprint arXiv:1802.06444, 2018 | 7 | 2018 |
| Category-based dynamic recommendations adaptive to user interest drifts K Lin, D Liu 2014 Sixth International Conference on Wireless Communications and Signal …, 2014 | 7 | 2014 |
Jiayu ZhouAssociate Professor at Michigan State UniversityDirección de correo verificada de cse.msu.edu
