Image de couverture de livre

OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Tyagi, Sahil, Cozma, Andrei, Kotevska, Olivera, Wang, Feiyi
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Artificial Intelligence Cryptography and Security Distributed, Parallel, and Cluster Computing
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning
par: Riya, Farhin Farhad, et autres
Publié: (2026)

BackFed: An Efficient & Standardized Benchmark Suite for Backdoor Attacks in Federated Learning
par: Dao, Thinh, et autres
Publié: (2025)

FedTrident: Resilient Road Condition Classification Against Poisoning Attacks in Federated Learning
par: Liu, Sheng, et autres
Publié: (2026)

FedGraM: Defending Against Untargeted Attacks in Federated Learning via Embedding Gram Matrix
par: Wu, Di, et autres
Publié: (2025)

FedAT: Federated Adversarial Training for Distributed Insider Threat Detection
par: Gayathri, R G, et autres
Publié: (2024)

Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications
par: Akhtarshenas, Azim, et autres
Publié: (2023)

Demo: FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning & Analytics
par: Geng, Jiaxiang, et autres
Publié: (2024)

FedBGS: A Blockchain Approach to Segment Gossip Learning in Decentralized Systems
par: Turazza, Fabio, et autres
Publié: (2026)

On Using Large-Batches in Federated Learning
par: Tyagi, Sahil
Publié: (2025)

On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions
par: Jimenez-Gutierrez, Daniel M., et autres
Publié: (2025)

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation
par: Herath, Charuka, et autres
Publié: (2025)

Vertical Federated Learning: Concepts, Advances and Challenges
par: Liu, Yang, et autres
Publié: (2022)

FedRKG: A Privacy-preserving Federated Recommendation Framework via Knowledge Graph Enhancement
par: Yao, Dezhong, et autres
Publié: (2024)

Inclusive, Differentially Private Federated Learning for Clinical Data
par: Parampottupadam, Santhosh, et autres
Publié: (2025)

BAFFLE: A Baseline of Backpropagation-Free Federated Learning
par: Feng, Haozhe, et autres
Publié: (2023)

Secure and Privacy-Preserving Vertical Federated Learning
par: Jin, Shan, et autres
Publié: (2026)

Trustworthy Federated Learning: Privacy, Security, and Beyond
par: Chen, Chunlu, et autres
Publié: (2024)

Celtibero: Robust Layered Aggregation for Federated Learning
par: Molina-Coronado, Borja
Publié: (2024)

Federated Learning for Cyber Physical Systems: A Comprehensive Survey
par: Quan, Minh K., et autres
Publié: (2025)

Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning
par: Ozfatura, Kerem, et autres
Publié: (2022)

An Adaptive Differential Privacy Method Based on Federated Learning
par: Wang, Zhiqiang, et autres
Publié: (2024)

Federated Learning with Blockchain-Enhanced Machine Unlearning: A Trustworthy Approach
par: Zuo, Xuhan, et autres
Publié: (2024)

POPri: Private Federated Learning using Preference-Optimized Synthetic Data
par: Hou, Charlie, et autres
Publié: (2025)

Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning
par: Zhang, Meiying, et autres
Publié: (2024)

FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
par: Lee, Younghan, et autres
Publié: (2024)

Byzantine-Robust Federated Learning Using Generative Adversarial Networks
par: Zafar, Usama, et autres
Publié: (2025)

StatAvg: Mitigating Data Heterogeneity in Federated Learning for Intrusion Detection Systems
par: Bouzinis, Pavlos S., et autres
Publié: (2024)

Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization
par: Zhang, Jianing, et autres
Publié: (2025)

LoRA-based Parameter-Efficient LLMs for Continuous Learning in Edge-based Malware Detection
par: Rondanini, Christian, et autres
Publié: (2026)

FedCert: Federated Accuracy Certification
par: Nguyen, Minh Hieu, et autres
Publié: (2024)

EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning
par: Li, Zhiqiang, et autres
Publié: (2025)

Federated Spatiotemporal Graph Learning for Passive Attack Detection in Smart Grids
par: Agha, Bochra Al, et autres
Publié: (2025)

GANcrop: A Contrastive Defense Against Backdoor Attacks in Federated Learning
par: Gan, Xiaoyun, et autres
Publié: (2024)

Enhancing Security in Federated Learning through Adaptive Consensus-Based Model Update Validation
par: Alsulaimawi, Zahir
Publié: (2024)

Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning
par: Liu, Ji, et autres
Publié: (2024)

Generative AI like ChatGPT in Blockchain Federated Learning: use cases, opportunities and future
par: Puppala, Sai, et autres
Publié: (2024)

SelectiveShield: Lightweight Hybrid Defense Against Gradient Leakage in Federated Learning
par: Li, Borui, et autres
Publié: (2025)

QuanCrypt-FL: Quantized Homomorphic Encryption with Pruning for Secure Federated Learning
par: Mia, Md Jueal, et autres
Publié: (2024)

FEDSTR: Money-In AI-Out | A Decentralized Marketplace for Federated Learning and LLM Training on the NOSTR Protocol
par: Nikolakakis, Konstantinos E., et autres
Publié: (2024)

FedBaF: Federated Learning Aggregation Biased by a Foundation Model
par: Park, Jong-Ik, et autres
Publié: (2024)