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Publication search results
found 113 matches
- 2023
- Junyi Zhu, Ruicong Yao, Matthew B. Blaschko:
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning. ICML 2023: 43228-43257 - Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang:
Personalized Subgraph Federated Learning. ICML 2023: 1396-1415 - Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He:
Optimizing the Collaboration Structure in Cross-Silo Federated Learning. ICML 2023: 1718-1736 - Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson:
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning. ICML 2023: 3757-3781 - Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan:
Fast Federated Machine Unlearning with Nonlinear Functional Theory. ICML 2023: 4241-4268 - Hanxiao Chen, Meng Hao, Hongwei Li, Kangjie Chen, Guowen Xu, Tianwei Zhang, Xilin Zhang:
GuardHFL: Privacy Guardian for Heterogeneous Federated Learning. ICML 2023: 4566-4584 - Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li:
Efficient Personalized Federated Learning via Sparse Model-Adaptation. ICML 2023: 5234-5256 - Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang:
On the Convergence of Federated Averaging with Cyclic Client Participation. ICML 2023: 5677-5721 - Edwige Cyffers, Aurélien Bellet, Debabrota Basu:
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. ICML 2023: 6683-6711 - Yanbo Dai, Songze Li:
Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning. ICML 2023: 6712-6725 - Ron Dorfman, Shay Vargaftik, Yaniv Ben-Itzhak, Kfir Yehuda Levy:
DoCoFL: Downlink Compression for Cross-Device Federated Learning. ICML 2023: 8356-8388 - Adrià Gascón, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh:
Federated Heavy Hitter Recovery under Linear Sketching. ICML 2023: 10997-11012 - Yongxin Guo, Xiaoying Tang, Tao Lin:
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction. ICML 2023: 12034-12054 - Zhishuai Guo, Rong Jin, Jiebo Luo, Tianbao Yang:
FeDXL: Provable Federated Learning for Deep X-Risk Optimization. ICML 2023: 11934-11966 - Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Michael G. Rabbat:
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design. ICML 2023: 11888-11904 - Yaming Guo, Kai Guo, Xiaofeng Cao, Tieru Wu, Yi Chang:
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships. ICML 2023: 11905-11933 - Minhui Huang, Dewei Zhang, Kaiyi Ji:
Achieving Linear Speedup in Non-IID Federated Bilevel Learning. ICML 2023: 14039-14059 - Ruiquan Huang, Huanyu Zhang, Luca Melis, Milan Shen, Meisam Hejazinia, Jing Yang:
Federated Linear Contextual Bandits with User-level Differential Privacy. ICML 2023: 14060-14095 - Pierre Humbert, Batiste Le Bars, Aurélien Bellet, Sylvain Arlot:
One-Shot Federated Conformal Prediction. ICML 2023: 14153-14177 - Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G. Edward Suh, Moinuddin K. Qureshi, Hsien-Hsin S. Lee:
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis. ICML 2023: 15884-15899 - Xiaoyun Li, Ping Li:
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation. ICML 2023: 19638-19688 - Xiaoxiao Li, Zhao Song, Jiaming Yang:
Federated Adversarial Learning: A Framework with Convergence Analysis. ICML 2023: 19932-19959 - Zexi Li, Tao Lin, Xinyi Shang, Chao Wu:
Revisiting Weighted Aggregation in Federated Learning with Neural Networks. ICML 2023: 19767-19788 - Songze Li, Duanyi Yao, Jin Liu:
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models. ICML 2023: 20296-20311 - Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael I. Jordan, Ramesh Raskar:
Federated Conformal Predictors for Distributed Uncertainty Quantification. ICML 2023: 22942-22964 - Peihua Mai, Yan Pang:
Vertical Federated Graph Neural Network for Recommender System. ICML 2023: 23516-23535 - Tanguy Marchand, Regis Loeb, Ulysse Marteau-Ferey, Jean Ogier du Terrail, Arthur Pignet:
SRATTA: Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning. ICML 2023: 23886-23914 - Kunjal Panchal, Sunav Choudhary, Subrata Mitra, Koyel Mukherjee, Somdeb Sarkhel, Saayan Mitra, Hui Guan:
Flash: Concept Drift Adaptation in Federated Learning. ICML 2023: 26931-26962 - Qi Pang, Lun Wang, Shuai Wang, Wenting Zheng, Dawn Song:
Secure Federated Correlation Test and Entropy Estimation. ICML 2023: 26990-27010 - Sejun Park, Kihun Hong, Ganguk Hwang:
Towards Understanding Ensemble Distillation in Federated Learning. ICML 2023: 27132-27187
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