NEURIPS 2025 "federated learning" Papers
38 papers found
A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments
Siyuan Wu, Yongzhe Jia, Haolong Xiang et al.
Bi-Directional Communication-Efficient Stochastic FL via Remote Source Generation
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh et al.
Class-wise Balancing Data Replay for Federated Class-Incremental Learning
Zhuang Qi, Ying-Peng Tang, Lei Meng et al.
Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning
Dipam Goswami, Simone Magistri, Kai Wang et al.
Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
Ming Wen, Jiaqi Zhu, Yuedong Xu et al.
Diffusion Federated Dataset
SEOKJU HAHN, Junghye Lee
DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
Yueyang Yuan, Wenke Huang, Guancheng Wan et al.
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
Efficient Federated Learning against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients
Shiyuan Zuo, Xingrun Yan, Rongfei Fan et al.
Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable
Bicheng Ying, Zhe Li, Haibo Yang
FedEL: Federated Elastic Learning for Heterogeneous Devices
Letian Zhang, Bo Chen, Jieming Bian et al.
FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
Li Zhang, Zhongxuan Han, XiaoHua Feng et al.
FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
Zhiqin Yang, Yonggang Zhang, Chenxin Li et al.
FedLPA: Local Prior Alignment for Heterogeneous Federated Generalized Category Discovery
Geeho Kim, Jinu Lee, Bohyung Han
FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
Yunbo Li, Jiaping Gui, Zhihang Deng et al.
FedRACE: A Hierarchical and Statistical Framework for Robust Federated Learning
Gang Yan, Sikai Yang, Wan Du
FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning
Fan Wu, Xinyu Yan, Jiabei Liu et al.
FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling
Hong Huang, Jinhai Yang, Yuan Chen et al.
FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
Pukang Ye, Luo Junwei, Jiachen Shen et al.
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.
Flick: Empowering Federated Learning with Commonsense Knowledge
Ran Zhu, Mingkun Yang, Shiqiang Wang et al.
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models
Yan Gao, Massimo R. Scamarcia, Javier Fernandez-Marques et al.
Gains: Fine-grained Federated Domain Adaptation in Open Set
Zhengyi Zhong, Wenzheng Jiang, Weidong Bao et al.
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
Jisoo Kim, Sungmin Kang, Sunwoo Lee
Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings
Yehya Farhat, Hamza ElMokhtar Shili, Fangshuo Liao et al.
MARS: A Malignity-Aware Backdoor Defense in Federated Learning
Wei Wan, Ning Yuxuan, Zhicong Huang et al.
Multiplayer Federated Learning: Reaching Equilibrium with Less Communication
TaeHo Yoon, Sayantan Choudhury, Nicolas Loizou
Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning
Arian Raje, Baris Askin, Divyansh Jhunjhunwala et al.
Rethinking Fair Federated Learning from Parameter and Client View
Kaiqi Guan, Wenke Huang, Xianda Guo et al.
Robust Federated Finetuning of LLMs via Alternating Optimization of LoRA
Shuangyi Chen, Yuanxin Guo, Yue Ju et al.
Sketched Gaussian Mechanism for Private Federated Learning
Qiaobo Li, Zhijie Chen, Arindam Banerjee
Soft-consensual Federated Learning for Data Heterogeneity via Multiple Paths
Sheng Huang, Lele Fu, Fanghua Ye et al.
SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
Haoyuan Liang, Shilei Cao, Li et al.
Streaming Federated Learning with Markovian Data
Khiem HUYNH, Malcolm Egan, Giovanni Neglia et al.
Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation
Xinghao Wu, Xuefeng Liu, Jianwei Niu et al.
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
Omri Lev, Vishwak Srinivasan, Moshe Shenfeld et al.
Tight Bounds for Maximum Weight Matroid Independent Set and Matching in the Zero Communication Model
Ilan Doron-Arad
You Only Communicate Once: One-shot Federated Low-Rank Adaptation of MLLM
Binqian Xu, Haiyang Mei, Zechen Bai et al.