IJCAI 2022 China 隐私计算与联邦学习论坛 (IJCAI 2022 China PCnFL)

时间 11月8日

特邀演讲：刘洋  “联邦学习系统中效率-安全-性能平衡探索”

12:00 – 12:30

特邀演讲：潘微科  “Cross-User Federated Recommendation”

1. Dazhong Rong, Qinming He and Jianhai Chen. Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios
2. Wei Wan, Shengshan Hu, Jianrong Lu, LEO YU ZHANG, Hai Jin and Yuanyuan He. Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection
3. Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai and Dejing Dou. FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server
4. Rufan Bai, Haoxing Lin, Xinyu Yang, Xiaowei Wu, Minming Li and Weijia Jia. Mixed Strategies for Security Games with General Defending Requirements
5. Xinyi Shang, Yang Lu, Gang Huang and Hanzi Wang. Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features
6. Qiang Shen, Haotian Feng, Rui Song, Stefano Teso, Fausto Giunchiglia and Hao Xu. Federated Multi-Task Attention for Cross-Individual Human Activity Recognition
7. Yuezhou Wu, Yan Kang, Jiahuan Luo, Yuanqin He and Qiang Yang. FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
8. Wenjie Li, Qiaolin Xia, Junfeng Deng, Hao Cheng, Jiangming Liu, Kouying Xue, Yong Cheng and Shu-Tao Xia. Achieving Lightweight Federated Advertising with Self-Supervised Split Distillation