2024 "federated learning" Papers

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.

Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients

Mengmeng Ma, Tang Li, Xi Peng

Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning

Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu et al.

Byzantine Resilient and Fast Federated Few-Shot Learning

Ankit Pratap Singh, Namrata Vaswani

Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates

Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui et al.

Certifiably Byzantine-Robust Federated Conformal Prediction

Mintong Kang, Zhen Lin, Jimeng Sun et al.

Clustered Federated Learning via Gradient-based Partitioning

Heasung Kim, Hyeji Kim, Gustavo De Veciana

COALA: A Practical and Vision-Centric Federated Learning Platform

Weiming Zhuang, Jian Xu, Chen Chen et al.

Collaborative Heterogeneous Causal Inference Beyond Meta-analysis

Tianyu Guo, Sai Praneeth Karimireddy, Michael Jordan

Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models

Zixin Zhang, Fan Qi, Changsheng Xu

Exploiting Label Skews in Federated Learning with Model Concatenation

Yiqun Diao, Qinbin Li, Bingsheng He

FADAS: Towards Federated Adaptive Asynchronous Optimization

Yujia Wang, Shiqiang Wang, Songtao Lu et al.

Fair Federated Learning via the Proportional Veto Core

Bhaskar Ray Chaudhury, Aniket Murhekar, Zhuowen Yuan et al.

FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update

Ji Liu, Juncheng Jia, Tianshi Che et al.

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

Shiwei Li, Wenchao Xu, Haozhao Wang et al.

FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models

Jingwei Sun, Ziyue Xu, Hongxu Yin et al.

FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler

Hongyi Peng, Han Yu, Xiaoli Tang et al.

FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants

Shanli Tan, Hao Cheng, Xiaohu Wu et al.

FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning

Haokun Chen, Yao Zhang, Denis Krompass et al.

FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels

Authors: Jichang Li, Guanbin Li, Hui Cheng et al.

Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning

Shangchao Su, Mingzhao Yang, Bin Li et al.

Federated Combinatorial Multi-Agent Multi-Armed Bandits

Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal

Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users

Hantao Yang, Xutong Liu, Zhiyong Wang et al.

Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes

Zhen Qin, Daoyuan Chen, Bingchen Qian et al.

Federated Learning with Extremely Noisy Clients via Negative Distillation

Yang Lu, Lin Chen, Yonggang Zhang et al.

Federated Neuro-Symbolic Learning

Pengwei Xing, Songtao Lu, Han Yu

Federated Optimization with Doubly Regularized Drift Correction

Xiaowen Jiang, Anton Rodomanov, Sebastian Stich

Federated Self-Explaining GNNs with Anti-shortcut Augmentations

Linan Yue, Qi Liu, Weibo Gao et al.

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning

Xinyuan Ji, Zhaowei Zhu, Wei Xi et al.

FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees

Jiahao Liu, Yipeng Zhou, Di Wu et al.

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing

Yongzhe Jia, Xuyun Zhang, Amin Beheshti et al.

FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning

Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity

Yiyue Chen, Haris Vikalo, Chianing Wang

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering

Yongxin Guo, Xiaoying Tang, Tao Lin

FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error

Yueqi Xie, Minghong Fang, Neil Gong

FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data

Shusen Jing, Anlan Yu, Shuai Zhang et al.

Formal Logic Enabled Personalized Federated Learning through Property Inference

Ziyan An, Taylor Johnson, Meiyi Ma

Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials

Jonathan Scott, Aine E Cahill

Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!

Milad Sefidgaran, Romain Chor, Abdellatif Zaidi et al.

Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization

Ziqing Fan, Shengchao Hu, Jiangchao Yao et al.

MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis

Luyuan Xie, Manqing Lin, Tianyu Luan et al.

Multi-Dimensional Fair Federated Learning

Cong Su, Guoxian Yu, Jun Wang et al.