• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 30 matches

• 2025
• 
  Yuhao Shen, Wei Xi, Yunyun Cai, Yuwei Fan, He Yang, Jizhong Zhao:
  Multi-objective federated learning: Balancing global performance and individual fairness. Future Gener. Comput. Syst. 162: 107468 (2025)
• 2024
• 
  José Á. Morell, Zakaria Abdelmoiz Dahi, Francisco Chicano, Gabriel Luque, Enrique Alba:
  A multi-objective approach for communication reduction in federated learning under devices heterogeneity constraints. Future Gener. Comput. Syst. 155: 367-383 (2024)
• 
  Yu Zhou, Lei Lei, Xiaohui Zhao, Lei You, Yaohua Sun, Symeon Chatzinotas:
  Decomposition and Meta-DRL Based Multi-Objective Optimization for Asynchronous Federated Learning in 6G-Satellite Systems. IEEE J. Sel. Areas Commun. 42(5): 1115-1129 (2024)
• 
  Narisu Cha, Long Chang:
  Multi-Objective Distributed Client Selection in Federated Learning-Assisted Internet of Vehicles. Sensors 24(13): 4180 (2024)
• 
  Renyou Xie, Chaojie Li, Xiaojun Zhou, Hongyang Chen, Zhaoyang Dong:
  Differentially Private Federated Learning for Multitask Objective Recognition. IEEE Trans. Ind. Informatics 20(5): 7269-7281 (2024)
• 
  Chunnan Wang, Xiangyu Shi, Hongzhi Wang:
  Fair Federated Learning with Multi-Objective Hyperparameter Optimization. ACM Trans. Knowl. Discov. Data 18(8): 208:1-208:13 (2024)
• 
  Xiaoli Tang, Han Yu:
  Multi-Session Multi-Objective Budget Optimization for Auction-based Federated Learning. IJCNN 2024: 1-8
• 
  Yu Zhou, Jingjing Guo, Haohui Li, Jinjin Tian, Xiaohui Zhao, Lei Lei:
  Efficient Federated Learning in 6G-Satellite Systems: Deep Reinforcement Learning Based Multi-Objective Optimization. WCNC 2024: 1-6
• 
  Narisu Cha, Long Chang:
  Distributed client selection with multi-objective in federated learning assisted Internet of Vehicles. CoRR abs/2401.03159 (2024)
• 
  Yan Kang, Ziyao Ren, Lixin Fan, Linghua Yang, Yongxin Tong, Qiang Yang:
  Hyperparameter Optimization for SecureBoost via Constrained Multi-Objective Federated Learning. CoRR abs/2404.04490 (2024)
• 2023
• 
  Zheng-Yi Chai, Chuandong Yang, Ya-Lun Li:
  Communication efficiency optimization in federated learning based on multi-objective evolutionary algorithm. Evol. Intell. 16(3): 1033-1044 (2023)
• 
  Tongyang Xu, Yuan Liu, Zhaotai Ma, Yiqiang Huang, Peng Liu:
  A DQN-Based Multi-Objective Participant Selection for Efficient Federated Learning. Future Internet 15(6): 209 (2023)
• 
  Fangyuan Zhao, Xuebin Ren, Shusen Yang, Peng Zhao, Rui Zhang, Xinxin Xu:
  Federated multi-objective reinforcement learning. Inf. Sci. 624: 811-832 (2023)
• 
  Yu Zhou, Xuemei Liu, Lei Lei:
  Multi-Objective Optimization for Bandwidth-Limited Federated Learning in Wireless Edge Systems. IEEE Open J. Commun. Soc. 4: 954-966 (2023)
• 
  Tan Li, Linqi Song:
  Federated Online Learning Aided Multi-Objective Proactive Caching in Heterogeneous Edge Networks. IEEE Trans. Cogn. Commun. Netw. 9(4): 1080-1095 (2023)
• 
  Benshun Yin, Zhiyong Chen, Meixia Tao:
  Predictive GAN-Powered Multi-Objective Optimization for Hybrid Federated Split Learning. IEEE Trans. Commun. 71(8): 4544-4560 (2023)
• 
  Yu Zhou, Xiaohui Zhao, Xuemei Liu, Lei You, Lei Lei:
  Efficient Federated Learning in Wireless Communication Systems: A Multi-Objective Optimization Perspective. ICCC 2023: 1-5
• 
  Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma:
  Federated Multi-Objective Learning. NeurIPS 2023
• 
  Yan Kang, Hanlin Gu, Xingxing Tang, Yuanqin He, Yuzhu Zhang, Jinnan He, Yuxing Han, Lixin Fan, Kai Chen, Qiang Yang:
  Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning. CoRR abs/2305.00312 (2023)
• 
  Ziyao Ren, Yan Kang, Lixin Fan, Linghua Yang, Tao Fan, Yongxin Tong, Qiang Yang:
  SecureBoost Hyperparameter Tuning via Multi-Objective Federated Learning. CoRR abs/2307.10579 (2023)
• 
  Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma:
  Federated Multi-Objective Learning. CoRR abs/2310.09866 (2023)
• 2022
• 
  Jialin Zhong, Yahui Wu, Wubin Ma, Su Deng, Haohao Zhou:
  Optimizing Multi-Objective Federated Learning on Non-IID Data with Improved NSGA-III and Hierarchical Clustering. Symmetry 14(5): 1070 (2022)
• 
  Zeou Hu, Kiarash Shaloudegi, Guojun Zhang, Yaoliang Yu:
  Federated Learning Meets Multi-Objective Optimization. IEEE Trans. Netw. Sci. Eng. 9(4): 2039-2051 (2022)
• 
  Xuezhen Tu, Kun Zhu:
  Learning-based Multi-Objective Resource Allocation for Over-the-Air Federated Learning. GLOBECOM 2022: 3065-3070
• 
  Ninareh Mehrabi, Cyprien de Lichy, John McKay, Cynthia He, William Campbell:
  Towards Multi-Objective Statistically Fair Federated Learning. CoRR abs/2201.09917 (2022)
• 
  Benshun Yin, Zhiyong Chen, Meixia Tao:
  Predictive GAN-powered Multi-Objective Optimization for Hybrid Federated Split Learning. CoRR abs/2209.02428 (2022)
• 2021
• 
  Yaochu Jin:
  Multi-objective Evolutionary Federated Learning. IoTBDS 2021: 5
• 2020
• 
  Hangyu Zhu, Yaochu Jin:
  Multi-Objective Evolutionary Federated Learning. IEEE Trans. Neural Networks Learn. Syst. 31(4): 1310-1322 (2020)
• 
  Zeou Hu, Kiarash Shaloudegi, Guojun Zhang, Yaoliang Yu:
  FedMGDA+: Federated Learning meets Multi-objective Optimization. CoRR abs/2006.11489 (2020)
• 2018
• 
  Hangyu Zhu, Yaochu Jin:
  Multi-objective Evolutionary Federated Learning. CoRR abs/1812.07478 (2018)