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Publication search results
found 36 matches
- 2023
- Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha:
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis. ICCV 2023: 4976-4985 - Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu:
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier. ICCV 2023: 5296-5306 - Jingwei Sun, Ziyue Xu, Dong Yang, Vishwesh Nath, Wenqi Li, Can Zhao, Daguang Xu, Yiran Chen, Holger R. Roth:
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples. ICCV 2023: 5180-5189 - Yu-Tong Cao, Ye Shi, Baosheng Yu, Jingya Wang, Dacheng Tao:
Knowledge-Aware Federated Active Learning with Non-IID Data. ICCV 2023: 22222-22232 - Haokun Chen, Ahmed Frikha, Denis Krompass, Jindong Gu, Volker Tresp:
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation. ICCV 2023: 4826-4836 - Rui Chen, Qiyu Wan, Pavana Prakash, Lan Zhang, Xu Yuan, Yanmin Gong, Xin Fu, Miao Pan:
Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization. ICCV 2023: 16953-16963 - Yae Jee Cho, Gauri Joshi, Dimitrios Dimitriadis:
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels. ICCV 2023: 17041-17050 - Tuong Do, Binh X. Nguyen, Vuong Pham, Toan Tran, Erman Tjiputra, Quang D. Tran, Anh Nguyen:
Reducing Training Time in Cross-Silo Federated Learning using Multigraph Topology. ICCV 2023: 19352-19362 - Xiuwen Fang, Mang Ye, Xiyuan Yang:
Robust Heterogeneous Federated Learning under Data Corruption. ICCV 2023: 4997-5007 - Chun-Mei Feng, Kai Yu, Nian Liu, Xinxing Xu, Salman Khan, Wangmeng Zuo:
Towards Instance-adaptive Inference for Federated Learning. ICCV 2023: 23230-23239 - Zahra Ghodsi, Mojan Javaheripi, Nojan Sheybani, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar:
zPROBE: Zero Peek Robustness Checks for Federated Learning. ICCV 2023: 4837-4847 - Jingwen Guo, Hong Liu, Shitong Sun, Tianyu Guo, Min Zhang, Chenyang Si:
FSAR: Federated Skeleton-based Action Recognition with Adaptive Topology Structure and Knowledge Distillation. ICCV 2023: 10366-10376 - Erdong Hu, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine:
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat. ICCV 2023: 19328-19339 - Siquan Huang, Yijiang Li, Chong Chen, Leyu Shi, Ying Gao:
Multi-metrics adaptively identifies backdoors in Federated learning. ICCV 2023: 4629-4639 - Hansol Kim, Youngjun Kwak, Minyoung Jung, Jinho Shin, Youngsung Kim, Changick Kim:
ProtoFL: Unsupervised Federated Learning via Prototypical Distillation. ICCV 2023: 6447-6456 - Jun Luo, Matías Mendieta, Chen Chen, Shandong Wu:
PGFed: Personalize Each Client's Global Objective for Federated Learning. ICCV 2023: 3923-3933 - Yasar Abbas Ur Rehman, Yan Gao, Pedro Porto Buarque de Gusmão, Mina Alibeigi, Jiajun Shen, Nicholas D. Lane:
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning. ICCV 2023: 16418-16427 - Guangyu Sun, Matías Mendieta, Jun Luo, Shandong Wu, Chen Chen:
FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning. ICCV 2023: 4965-4975 - Saeed Vahidian, Sreevatsank Kadaveru, Woonjoon Baek, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah, Bill Lin:
When Do Curricula Work in Federated Learning? ICCV 2023: 5061-5071 - Guangnian Wan, Haitao Du, Xuejing Yuan, Jun Yang, Meiling Chen, Jie Xu:
Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation. ICCV 2023: 4749-4758 - Xinghao Wu, Xuefeng Liu, Jianwei Niu, Guogang Zhu, Shaojie Tang:
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration. ICCV 2023: 19318-19327 - Haifeng Xia, Kai Li, Zhengming Ding:
Personalized Semantics Excitation for Federated Image Classification. ICCV 2023: 19244-19253 - Fu-En Yang, Chien-Yi Wang, Yu-Chiang Frank Wang:
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation. ICCV 2023: 19102-19111 - Chen Yang, Meilu Zhu, Yifan Liu, Yixuan Yuan:
FedPD: Federated Open Set Recognition with Parameter Disentanglement. ICCV 2023: 4859-4868 - Yaopei Zeng, Lei Liu, Li Liu, Li Shen, Shaoguo Liu, Baoyuan Wu:
Global Balanced Experts for Federated Long-Tailed Learning. ICCV 2023: 4792-4802 - Jie Zhang, Chen Chen, Weiming Zhuang, Lingjuan Lyu:
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation. ICCV 2023: 4759-4770 - Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Jian Cao, Haibing Guan:
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning. ICCV 2023: 5018-5028 - Chi Zhang, Xiaoman Zhang, Ekanut Sotthiwat, Yanyu Xu, Ping Liu, Liangli Zhen, Yong Liu:
Generative Gradient Inversion via Over-Parameterized Networks in Federated Learning. ICCV 2023: 5103-5112 - Yuhao Zhou, Mingjia Shi, Yuanxi Li, Yanan Sun, Qing Ye, Jiancheng Lv:
Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence. ICCV 2023: 5008-5017 - Weiming Zhuang, Yonggang Wen, Lingjuan Lyu, Shuai Zhang:
MAS: Towards Resource-Efficient Federated Multiple-Task Learning. ICCV 2023: 23357-23367
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