Federated Prompt Cooperation

Federated prompt cooperation explores collaborative machine learning across decentralized datasets, aiming to train shared models while preserving data privacy and addressing data heterogeneity. Current research focuses on adapting various model architectures, including variational autoencoders, transformers, and reinforcement learning algorithms, to this federated setting, often employing techniques like low-rank adaptation and prompt engineering to manage communication overhead and improve model personalization. This approach holds significant promise for applications requiring distributed data analysis, such as healthcare, industrial IoT, and social network analysis, by enabling the development of more accurate and robust models while respecting data privacy constraints.

Papers

January 9, 2025

TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
Runhua Xu, Bo Li, Chao Li, James B.D. Joshi, Shuai Ma, Jianxin Li
LeArning Abstract Federated Prompt Cooperation Secure Aggregation Inference Attack Single Tap Functional Encryption

December 30, 2024

Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection
Hongrui Shi, Valentin Radu, Po Yang
Training Data Federated Learning Federated Prompt Cooperation Data Selection Device Training Client Model

December 18, 2024

December 16, 2024

F-RBA: A Federated Learning-based Framework for Risk-based Authentication
Hamidreza Fereidouni, Abdelhakim Senhaji Hafid, Dimitrios Makrakis, Yaser Baseri
Federated Prompt Cooperation Learning Framework Identity Verification Federated Approach Authentication Scheme Two Factor Authentication

December 14, 2024

Adaptive Quantization Resolution and Power Control for Federated Learning over Cell-free Networks
Afsaneh Mahmoudi, Emil Björnson
LeArning Abstract Wireless Network Federated Prompt Cooperation Uplink Control Power Control Adaptive Quantization Cell Free

December 13, 2024

Temporal Causal Discovery in Dynamic Bayesian Networks Using Federated Learning
Jianhong Chen, Ying Ma, Xubo Yue
LeArning Abstract Optimization Purpose Federated Prompt Cooperation Structure Learning Continuous Optimization Dynamic Bayesian Network Temporal Causal Discovery

December 2, 2024

November 30, 2024

Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels
Yuxin Tian, Mouxing Yang, Yuhao Zhou, Jian Wang, Qing Ye, Tongliang Liu, Gang Niu, Jiancheng Lv
Noisy Label Federated Prompt Cooperation Local Learning Similarity Regularization Label Noise Robustness

November 28, 2024

PEFT-as-an-Attack! Jailbreaking Language Models during Federated Parameter-Efficient Fine-Tuning
Shenghui Li, Edith C.-H. Ngai, Fanghua Ye, Thiemo Voigt
Language Model Fine Tuning Parameter Efficient Fine Tuning Federated Prompt Cooperation

November 25, 2024

TIFeD: a Tiny Integer-based Federated learning algorithm with Direct feedback alignment
Luca Colombo, Alessandro Falcetta, Manuel Roveri
Deep Learning Model Practical Algorithm Federated Prompt Cooperation Resource Constrained Device Feedback Alignment

November 24, 2024

Modality Alignment Meets Federated Broadcasting
Yuting Ma, Shengeng Tang, Xiaohua Xu, Lechao Cheng
Federated Prompt Cooperation Modality Alignment

November 22, 2024

November 18, 2024

Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors
Shovito Barua Soumma, S M Raihanul Alam, Rudmila Rahman, Umme Niraj Mahi, Sayyed Mostafa Mostafavi, Hassan Ghasemzadeh
Federated Prompt Cooperation Wearable Sensor Gait Pattern Adaptive Freezing Gait Detection Synthetic Fog Gramian Angular Field Freezing of Gait

November 17, 2024

Efficient Federated Unlearning with Adaptive Differential Privacy Preservation
Yu Jiang, Xindi Tong, Ziyao Liu, Huanyi Ye, Chee Wei Tan, Kwok-Yan Lam
Unlearning Framework Federated Prompt Cooperation Harmful Unlearning Federated Unlearning Adaptive Differential Privacy

November 16, 2024

How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution
Jinbo Wang, Ruijin Wang, Fengli Zhang
LeArning Abstract Natural Gradient Federated Prompt Cooperation Model Poisoning Attack Aggregated Gradient New Solution

November 12, 2024

Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks
Tianqu Kang, Zixin Wang, Hengtao He, Jun Zhang, Shenghui Song, Khaled B. Letaief
Differential Privacy Network Programming Adaptation Concern Federated Prompt Cooperation Wireless System

November 7, 2024

Fed-LDR: Federated Local Data-infused Graph Creation with Node-centric Model Refinement
Jiechao Gao, Yuangang Li, Syeda Faiza Ahmed
Federated Prompt Cooperation Model Improvement Internet of Thing Environment Federated Graph Learning Urban Network

Federated Prompt Cooperation

Papers

TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning

Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection

Covariances for Free: Exploiting Mean Distributions for Federated Learning with Pre-Trained Models

Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data

F-RBA: A Federated Learning-based Framework for Risk-based Authentication

Adaptive Quantization Resolution and Power Control for Federated Learning over Cell-free Networks

Temporal Causal Discovery in Dynamic Bayesian Networks Using Federated Learning

Refined Analysis of Federated Averaging's Bias and Federated Richardson-Romberg Extrapolation

HumekaFL: Automated Detection of Neonatal Asphyxia Using Federated Learning

Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels

PEFT-as-an-Attack! Jailbreaking Language Models during Federated Parameter-Efficient Fine-Tuning

TIFeD: a Tiny Integer-based Federated learning algorithm with Direct feedback alignment

Modality Alignment Meets Federated Broadcasting

LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement

Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning

Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors

Efficient Federated Unlearning with Adaptive Differential Privacy Preservation

How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution

Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks

Fed-LDR: Federated Local Data-infused Graph Creation with Node-centric Model Refinement