4. Y. Gong, Y. Li, and N. Freris, “FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity.” Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE), pp. 2575-2587, May 2022.
点击次数：
是否译文：否
上一条： 3. X. Wang, B. Tan, Y. Guo, T. Yang, D. Huang, L. Xu, N. Freris, H. Zhou, and X. Li, “CONFLUX: A Request-level Fusion Framework for Impression Allocation via Cascade Distillation.” Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 4070–4078, Aug. 2022.
下一条： 5. T. Wen, Y. Zhang, and N. Freris, “PF-MOT: Probability Fusion Based 3D Multi-Object Tracking for Autonomous Vehicles.” Proceedings of the 39th International Conference on Robotics and Applications (ICRA), pp. 700-706, May 2022.