"federated learning" Papers
178 papers found • Page 2 of 4
Conference
FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
Seung-Wook Kim, Seongyeol Kim, Jiah Kim 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.
Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning
Yanbiao Ma, Wei Dai, Wenke Huang et al.
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection
Lei Shen, Zhenheng Tang, Lijun Wu et al.
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
Ye Li, Yanchao Zhao, chengcheng zhu et al.
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
Jisoo Kim, Sungmin Kang, Sunwoo Lee
Learn How to Query from Unlabeled Data Streams in Federated Learning
Yuchang Sun, Xinran Li, Tao Lin et al.
Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings
Yehya Farhat, Hamza ElMokhtar Shili, Fangshuo Liao et al.
LiD-FL: Towards List-Decodable Federated Learning
Hong Liu, Liren Shan, Han Bao et al.
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement
Jieming Bian, Lei Wang, Letian Zhang et al.
Many-Objective Multi-Solution Transport
Ziyue Li, Tian Li, Virginia Smith et al.
MARS: A Malignity-Aware Backdoor Defense in Federated Learning
Wei Wan, Ning Yuxuan, Zhicong Huang et al.
Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach
Chunxu Zhang, Guodong Long, Hongkuan Guo et al.
Multiplayer Federated Learning: Reaching Equilibrium with Less Communication
TaeHo Yoon, Sayantan Choudhury, Nicolas Loizou
NoT: Federated Unlearning via Weight Negation
Yasser Khalil, Leo Maxime Brunswic, Soufiane Lamghari et al.
On the Robustness of Distributed Machine Learning Against Transfer Attacks
Sebastien Andreina, Pascal Zimmer, Ghassan Karame
OpenFLAME: Federated Visual Positioning System to Enable Large-Scale Augmented Reality Applications
Sagar Bharadwaj Kalasibail Seetharam, Harrison Williams, Ainiu Luke Wang et al.
Optimization with Access to Auxiliary Information
EL MAHDI CHAYTI, Sai Karimireddy
Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model
Ziyuan Yang, Yingyu Chen, Zhiwen Wang et al.
Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach
Qingxiang Liu, Sheng Sun, Yuxuan Liang et al.
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
Problem-Parameter-Free Federated Learning
Wenjing Yan, Kai Zhang, Xiaolu Wang et al.
Query-based Knowledge Transfer for Heterogeneous Learning Environments
Norah Alballa, Wenxuan Zhang, Ziquan Liu et al.
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.
SparsyFed: Sparse Adaptive Federated Learning
Adriano Guastella, Lorenzo Sani, Alex Iacob 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.
Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness
Haoming Wang, Wei Gao
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
Towards Federated RLHF with Aggregated Client Preference for LLMs
Feijie Wu, Xiaoze Liu, Haoyu Wang et al.
TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning
Gangqiang Hu, Jianfeng Lu, Jianmin Han et al.
You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data
Shanshan Yan, Zexi Li, Chao Wu et al.
You Only Communicate Once: One-shot Federated Low-Rank Adaptation of MLLM
Binqian Xu, Haiyang Mei, Zechen Bai et al.
Accelerating Federated Learning with Quick Distributed Mean Estimation
Ran Ben Basat, Shay Vargaftik, Amit Portnoy et al.
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers
Eros Fanì, Raffaello Camoriano, Barbara Caputo et al.
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning
Do-Yeon Kim, Dong-Jun Han, Jun Seo et al.
Adaptive Group Personalization for Federated Mutual Transfer Learning
Haoqing Xu, Dian Shen, Meng Wang et al.
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
Hongchang Gao
AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning
Dong Chen, Hongyuan Qu, Guangwu Xu
A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization
Xinwen Zhang, Ali Payani, Myungjin Lee et al.
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen et al.
Balancing Similarity and Complementarity for Federated Learning
Kunda Yan, Sen Cui, Abudukelimu Wuerkaixi et al.