Cover Image

DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jia, Yongzhe, Zhang, Xuyun, Hu, Hongsheng, Choo, Kim-Kwang Raymond, Qi, Lianyong, Xu, Xiaolong, Beheshti, Amin, Dou, Wanchun
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing
by: Jia, Yongzhe, et al.
Published: (2024)

Shadow-Free Membership Inference Attacks: Recommender Systems Are More Vulnerable Than You Thought
by: Chi, Xiaoxiao, et al.
Published: (2024)

Reference Recommendation based Membership Inference Attack against Hybrid-based Recommender Systems
by: Chi, Xiaoxiao, et al.
Published: (2025)

Reward-Driven Interaction: Enhancing Proactive Dialogue Agents through User Satisfaction Prediction
by: Shen, Wei, et al.
Published: (2025)

MTP: Exploring Multimodal Urban Traffic Profiling with Modality Augmentation and Spectrum Fusion
by: Xiang, Haolong, et al.
Published: (2025)

Policy Filtration for RLHF to Mitigate Noise in Reward Models
by: Zhang, Chuheng, et al.
Published: (2024)

Special Issue on “Ensuring security for artificial intelligence applications in mobile edge computing software systems”
by: Lianyong Qi, et al.
Published: (2024)

Natural Language-Oriented Programming (NLOP): Towards Democratizing Software Creation
by: Beheshti, Amin
Published: (2024)

Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learning
by: Li, Yanli, et al.
Published: (2024)

SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices
by: Zhong, Zhengyi, et al.
Published: (2025)

Democratizing AI in Africa: FL for Low-Resource Edge Devices
by: Fabila, Jorge, et al.
Published: (2024)

EASTER: Embedding Aggregation-based Heterogeneous Models Training in Vertical Federated Learning
by: Wang, Shuo, et al.
Published: (2023)

AdaptiveFL: Adaptive Heterogeneous Federated Learning for Resource-Constrained AIoT Systems
by: Jia, Chentao, et al.
Published: (2023)

PersoPilot: An Adaptive AI-Copilot for Transparent Contextualized Persona Classification and Personalized Response Generation
by: Afzoon, Saleh, et al.
Published: (2026)

FlexFL: Heterogeneous Federated Learning via APoZ-Guided Flexible Pruning in Uncertain Scenarios
by: Chen, Zekai, et al.
Published: (2024)

Robust Federated Learning on Edge Devices with Domain Heterogeneity
by: Le, Huy Q., et al.
Published: (2025)

QuanCrypt-FL: Quantized Homomorphic Encryption with Pruning for Secure Federated Learning
by: Mia, Md Jueal, et al.
Published: (2024)

Feature-Selective Representation Misdirection for Machine Unlearning
by: Chen, Taozhao, et al.
Published: (2025)

Agentic Adversarial Rewriting Exposes Architectural Vulnerabilities in Black-Box NLP Pipelines
by: Bethany, Mazal, et al.
Published: (2026)

EdgeFusion: On-Device Text-to-Image Generation
by: Castells, Thibault, et al.
Published: (2024)

FedDPG: An Adaptive Yet Efficient Prompt-tuning Approach in Federated Learning Settings
by: Shakeri, Ali, et al.
Published: (2025)

Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data
by: Liu, Ji, et al.
Published: (2024)

Skewness-Guided Pruning of Multimodal Swin Transformers for Federated Skin Lesion Classification on Edge Devices
by: Paxton, Kuniko, et al.
Published: (2025)

DeepFusion: Accelerating MoE Training via Federated Knowledge Distillation from Heterogeneous Edge Devices
by: Li, Songyuan, et al.
Published: (2026)

Generating Image Adversarial Examples by Embedding Digital Watermarks
by: Xiang, Yuexin, et al.
Published: (2020)

A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learning
by: Xiang, Yuexin, et al.
Published: (2021)

WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling
by: Su, Huai-an, et al.
Published: (2024)

GitFL: Adaptive Asynchronous Federated Learning using Version Control
by: Hu, Ming, et al.
Published: (2022)

CDKT-FL: Cross-Device Knowledge Transfer using Proxy Dataset in Federated Learning
by: Le, Huy Q., et al.
Published: (2022)

IP-FL: Incentivized and Personalized Federated Learning
by: Khan, Ahmad Faraz, et al.
Published: (2023)

`Do as I say not as I do': A Semi-Automated Approach for Jailbreak Prompt Attack against Multimodal LLMs
by: Chiu, Chun Wai, et al.
Published: (2025)

Watermarking Text Data on Large Language Models for Dataset Copyright
by: Liu, Yixin, et al.
Published: (2023)

Socially Beneficial Metaverse: Framework, Technologies, Applications, and Challenges
by: Xu, Xiaolong, et al.
Published: (2023)

CCVA-FL: Cross-Client Variations Adaptive Federated Learning for Medical Imaging
by: Gupta, Sunny, et al.
Published: (2024)

FL-XAI-ER: Federated Learning with Explainable AI For Energy-Renewable Edge Cloud Computing
by: Jena, Soumya Ranjan
Published: (2026)

CroSatFL: Energy-Efficient Federated Learning with Cross-Aggregation for Satellite Edge Computing
by: Yang, Nan, et al.
Published: (2026)

QuantFL: Sustainable Federated Learning for Edge IoT via Pre-Trained Model Quantisation
by: Herath, Charuka, et al.
Published: (2026)

CacheFL: Privacy-Preserving and Efficient Federated Cache Model Fine-Tuning for Vision-Language Models
by: Yi, Mengjun, et al.
Published: (2025)

Ratas framework: A comprehensive genai-based approach to rubric-based marking of real-world textual exams
by: Safilian, Masoud, et al.
Published: (2025)

Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses
by: Ferrag, Mohamed Amine, et al.
Published: (2023)