Personalized Federated Learning

Personalized federated learning (PFL) aims to train customized machine learning models for individual clients in a distributed setting, preserving data privacy. Current research emphasizes efficient aggregation techniques, often employing backbone self-distillation, generative parameter aggregation, or class-wise averaging, to balance personalization with global knowledge sharing and address data heterogeneity. This field is significant because it enables the development of more accurate and adaptable models across diverse applications while maintaining user privacy, particularly relevant in healthcare, autonomous driving, and other sensitive data domains.

Papers

June 20, 2023

Personalized Federated Learning with Feature Alignment and Classifier Collaboration
Jian Xu, Xinyi Tong, Shao-Lun Huang
Personalized Federated Learning Feature Alignment Global Semantic Classification Head

May 25, 2023

pFedSim: Similarity-Aware Model Aggregation Towards Personalized Federated Learning
Jiahao Tan, Yipeng Zhou, Gang Liu, Jessie Hui Wang, Shui Yu
Data Heterogeneity Personalized Federated Learning Model Aggregation Aspect Term Extraction Client Heterogeneity

May 10, 2023

FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment
Jiahao Liu, Jiang Wu, Jinyu Chen, Miao Hu, Yipeng Zhou, Di Wu
Federated Learning Personalized Federated Learning Personalized Model Weight Aggregation Weight Adjustment

May 9, 2023

Collaborative Chinese Text Recognition with Personalized Federated Learning
Shangchao Su, Haiyang Yu, Bin Li, Xiangyang Xue
Privacy Preserving Personalized Federated Learning Chinese Text Recognition

May 1, 2023

Personalized Federated Learning under Mixture of Distributions
Yue Wu, Shuaicheng Zhang, Wenchao Yu, Yanchi Liu, Quanquan Gu, Dawei Zhou, Haifeng Chen, Wei Cheng
Mixture Component Personalized Federated Learning Gaussian Mixture Model Covariate Shift Statistical Heterogeneity

April 25, 2023

Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM
Ziba Parsons, Fei Dou, Houyi Du, Zheng Song, Jin Lu
Personalized Federated Learning ADMM Algorithm Heterogeneous Environment Generic Stochastic

April 23, 2023

Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization
Rongfeng Pan, Jianzong Wang, Lingwei Kong, Zhangcheng Huang, Jing Xiao
Differential Privacy Text Summarization Personalized Federated Learning Gradient Modulation Information Aggregation

April 16, 2023

Federated Learning of Shareable Bases for Personalization-Friendly Image Classification
Hong-You Chen, Jike Zhong, Mingda Zhang, Xuhui Jia, Hang Qi, Boqing Gong, Wei-Lun Chao, Li Zhang
Image Classification Personalized Federated Learning Model Weight Image Personalization

April 11, 2023

Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model
Yixuan Liu, Suyun Zhao, Li Xiong, Yuhan Liu, Hong Chen
Personalized Federated Learning Thy Neighbor Shuffle Model Privacy Amplification Model Privacy

April 2, 2023

Personalized Federated Learning with Local Attention
Sicong Liang, Junchao Tian, Shujun Yang, Yu Zhang
Personalized Federated Learning Local Context pFL Method Heterogeneous Label Personalized Attention

March 27, 2023

Personalized Federated Learning on Long-Tailed Data via Adversarial Feature Augmentation
Yang Lu, Pinxin Qian, Gang Huang, Hanzi Wang
Adversarial Example Personalized Federated Learning Long Tailed Data Personalized Model Adversarial Style Augmentation

March 19, 2023

Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks
Chaoqun You, Kun Guo, Howard H. Yang, Tony Q. S. Quek
Federated Learning Edge Computing Personalized Federated Learning Mobile Edge Computing

March 15, 2023

Visual Prompt Based Personalized Federated Learning
Guanghao Li, Wansen Wu, Yan Sun, Li Shen, Baoyuan Wu, Dacheng Tao
Personalized Federated Learning Image Classification Task Personalized Model Federated Prompt Personalization Layer

February 23, 2023

Personalized Decentralized Federated Learning with Knowledge Distillation
Eunjeong Jeong, Marios Kountouris
Knowledge Distillation Personalized Federated Learning Decentralized Federated Learning Decentralized Network

February 21, 2023

Fusion of Global and Local Knowledge for Personalized Federated Learning
Tiansheng Huang, Li Shen, Yan Sun, Weiwei Lin, Dacheng Tao
World Event Hybrid Fusion Personalized Federated Learning Local Feature Sparse Decomposition

February 15, 2023

FedABC: Targeting Fair Competition in Personalized Federated Learning
Dui Wang, Li Shen, Yong Luo, Han Hu, Kehua Su, Yonggang Wen, Dacheng Tao
Class Imbalance Personalized Federated Learning Federated Averaging Binary Classification Loss Personalized Interpretable

February 13, 2023

PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees
Chulin Xie, De-An Huang, Wenda Chu, Daguang Xu, Chaowei Xiao, Bo Li, Anima Anandkumar
Personalized Federated Learning Generalization Guarantee pFL Method Better Out of Distribution Generalization

February 6, 2023

Cross-Fusion Rule for Personalized Federated Learning
Wangzhuo Yang, Bo Chen, Yijun Shen, Jiong Liu, Li Yu
Personalized Federated Learning Model Fusion Fusion Weight Fusion Strategy Fusion Layer

February 3, 2023

Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks
Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng
Native Robustness Backdoor Attack Personalized Federated Learning Better Robustness

December 5, 2022

Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics
Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura Cruz, Kerrie Douglas, Andrew Lan, Christopher Brinton
Personalized Federated Learning Mitigating Bias Student Model

Personalized Federated Learning

Papers

Personalized Federated Learning with Feature Alignment and Classifier Collaboration

pFedSim: Similarity-Aware Model Aggregation Towards Personalized Federated Learning

FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment

Collaborative Chinese Text Recognition with Personalized Federated Learning

Personalized Federated Learning under Mixture of Distributions

Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM

Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization

Federated Learning of Shareable Bases for Personalization-Friendly Image Classification

Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model

Personalized Federated Learning with Local Attention

Personalized Federated Learning on Long-Tailed Data via Adversarial Feature Augmentation

Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks

Visual Prompt Based Personalized Federated Learning

Personalized Decentralized Federated Learning with Knowledge Distillation

Fusion of Global and Local Knowledge for Personalized Federated Learning

FedABC: Targeting Fair Competition in Personalized Federated Learning

PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees

Cross-Fusion Rule for Personalized Federated Learning

Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks

Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics