Kaiyang Guo - RankMe

22 papers A* 3B 2Journal 14Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FedBNR: A Fully Global Federated Gaussian Process. Mach. Learn. Haolin Yu, Kaiyang Guo, Mahdi Karami, Guojun Zhang, Hongliang Li, Xi Chen, Pascal Poupart
2025	J	`jnl`	Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents. CoRR Yihong Tang, Kehai Chen, Liang Yue, Jinxin Fan, Caishen Zhou, Xiaoguang Li, Yuyang Zhang, Mingming Zhao, Shixiong Kai, Kaiyang Guo, Xingshan Zeng, Wenjing Cun, Lifeng Shang, Min Zhang
2025	J	`jnl`	Generative Models in Decision Making: A Survey. CoRR Yinchuan Li, Xinyu Shao, Jianping Zhang, Haozhi Wang, Leo Maxime Brunswic, Kaiwen Zhou, Jiqian Dong, Kaiyang Guo, Xiu Li, Zhitang Chen, Jun Wang, Jianye Hao
2025	J	`jnl`	Power control for D2D communication underlaying cellular networks based on deep Q-learning and fractional frequency reuse. J. Commun. Networks Tingting Yang, Yingqi Zhao, Jin Jin, Kaiyang Guo
2025	J	`jnl`	Proximalized Preference Optimization for Diverse Feedback Types: A Decomposed Perspective on DPO. CoRR Kaiyang Guo, Yinchuan Li, Zhitang Chen
2024	A*	`conf`	Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space. AAAI Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart
2023	J	`jnl`	Analysis of Line-of-Sight Angle Characteristics for Intercepting a Non-Maneuvering Target With Impact Angle Constraints. IEEE Access Xin Sun, Hui Wang, Kaiyang Guo, Yuru Bin, Heting Wang, Keqing Guo
2023	J	`jnl`	Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space. CoRR Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart
2022	J	`jnl`	Federated Bayesian Neural Regression: A Scalable Global Federated Gaussian Process. CoRR Haolin Yu, Kaiyang Guo, Mahdi Karami, Xi Chen, Guojun Zhang, Pascal Poupart
2022	—	`conf`	Information dissemination model of recommendation platform based on network community. DSC Riming Wu, Yiliang Han, Kaiyang Guo, Kai Liu
2022	A*	`conf`	Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief. NeurIPS Kaiyang Guo, Yunfeng Shao, Yanhui Geng
2022	J	`jnl`	Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief. CoRR Kaiyang Guo, Yunfeng Shao, Yanhui Geng
2022	A*	`conf`	Personalized Federated Learning via Variational Bayesian Inference. ICML Xu Zhang, Yinchuan Li, Wenpeng Li, Kaiyang Guo, Yunfeng Shao
2022	J	`jnl`	Personalized Federated Learning via Variational Bayesian Inference. CoRR Xu Zhang, Yinchuan Li, Wenpeng Li, Kaiyang Guo, Yunfeng Shao
2022	J	`jnl`	Robust One Round Federated Learning with Predictive Space Bayesian Inference. CoRR Mohsin Hasan, Zehao Zhang, Kaiyang Guo, Mahdi Karami, Guojun Zhang, Xi Chen, Pascal Poupart
2021	—	`conf`	Hierarchical Identity-Based Conditional Proxy Re-encryption Scheme Based RLWE and NTRU Variant. ICPCSEE (2) Chao Wang, Yiliang Han, Xiaowei Duan, Kaiyang Guo
2019	J	`jnl`	Temporal-Spatial Recommendation for Caching at Base Stations via Deep Reinforcement Learning. IEEE Access Kaiyang Guo, Chenyang Yang
2018	J	`jnl`	Interference Coordination and Resource Allocation Planning With Predicted Average Channel Gains for HetNets. IEEE Access Kaiyang Guo, Tingting Liu, Chenyang Yang, Zixiang Xiong
2018	J	`jnl`	Jointly Optimizing User Association and BS Muting for Cache-Enabled Networks With Network-Coded Multicast and Reconstructed Interference Cancelation. IEEE Trans. Commun. Kaiyang Guo, Chenyang Yang, Tingting Liu, Zixiang Xiong
2017	B	`conf`	Caching in Base Station with Recommendation via Q-Learning. WCNC Kaiyang Guo, Chenyang Yang, Tingting Liu
2017	—	`conf`	Efficient Order-Sensitive Activity Trajectory Search. WISE (1) Kaiyang Guo, Rong-Hua Li, Shaojie Qiao, Zhenjun Li, Weipeng Zhang, Minhua Lu
2017	B	`conf`	Interference management by exploiting cached files at users. PIMRC Kaiyang Guo, Chenyang Yang, Tingting Liu