Copertina

BlendFL: Blended Federated Learning for Handling Multimodal Data Heterogeneity

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Guerra-Manzanares, Alejandro, El-Herraoui, Omar, Maniatakos, Michail, Shamout, Farah E.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Privacy-preserving machine learning for healthcare: open challenges and future perspectives
di: Guerra-Manzanares, Alejandro, et al.
Pubblicazione: (2023)

MILES: Modality-Informed Learning Rate Scheduler for Balancing Multimodal Learning
di: Guerra-Manzanares, Alejandro, et al.
Pubblicazione: (2025)

MIND: Modality-Informed Knowledge Distillation Framework for Multimodal Clinical Prediction Tasks
di: Guerra-Manzanares, Alejandro, et al.
Pubblicazione: (2025)

Multi-modal Masked Siamese Network Improves Chest X-Ray Representation Learning
di: Shurrab, Saeed, et al.
Pubblicazione: (2024)

DRAUN: An Algorithm-Agnostic Data Reconstruction Attack on Federated Unlearning Systems
di: Lamri, Hithem, et al.
Pubblicazione: (2025)

Fully Decentralized Certified Unlearning
di: Lamri, Hithem, et al.
Pubblicazione: (2025)

Data-Driven Priors for Uncertainty-Aware Deterioration Risk Prediction with Multimodal Data
di: López, L. Julián Lechuga, et al.
Pubblicazione: (2026)

MixtureKit: A General Framework for Composing, Training, and Visualizing Mixture-of-Experts Models
di: Chamma, Ahmad, et al.
Pubblicazione: (2025)

ReVeil: Unconstrained Concealed Backdoor Attack on Deep Neural Networks using Machine Unlearning
di: Alam, Manaar, et al.
Pubblicazione: (2025)

FedDPC : Handling Data Heterogeneity and Partial Client Participation in Federated Learning
di: Sen, Mrinmay, et al.
Pubblicazione: (2025)

EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records
di: Shurrab, Saeed, et al.
Pubblicazione: (2026)

Cross-Lingual Empirical Evaluation of Large Language Models for Arabic Medical Tasks
di: Abouzahir, Chaimae, et al.
Pubblicazione: (2026)

MI$^2$DAS: A Multi-Layer Intrusion Detection Framework with Incremental Learning for Securing Industrial IoT Networks
di: Lian, Wei, et al.
Pubblicazione: (2026)

NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients
di: Kang, Honggu, et al.
Pubblicazione: (2023)

Hybrid Memory Replay: Blending Real and Distilled Data for Class Incremental Learning
di: Kong, Jiangtao, et al.
Pubblicazione: (2024)

Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object Detection
di: Khalil, Ahmad, et al.
Pubblicazione: (2024)

The Role of Functional Muscle Networks in Improving Hand Gesture Perception for Human-Machine Interfaces
di: Armanini, Costanza, et al.
Pubblicazione: (2024)

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms
di: Peng, Yuanzhe, et al.
Pubblicazione: (2025)

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

Improving Offline RL by Blending Heuristics
di: Geng, Sinong, et al.
Pubblicazione: (2023)

LLMPot: Dynamically Configured LLM-based Honeypot for Industrial Protocol and Physical Process Emulation
di: Vasilatos, Christoforos, et al.
Pubblicazione: (2024)

Beyond Modality Collapse: Representations Blending for Multimodal Dataset Distillation
di: Zhang, Xin, et al.
Pubblicazione: (2025)

Exploring Robust Intrusion Detection: A Benchmark Study of Feature Transferability in IoT Botnet Attack Detection
di: Guerra-Manzanares, Alejandro, et al.
Pubblicazione: (2026)

Meta-FL: A Novel Meta-Learning Framework for Optimizing Heterogeneous Model Aggregation in Federated Learning
di: Alsulaimawi, Zahir
Pubblicazione: (2024)

CHEHAB RL: Learning to Optimize Fully Homomorphic Encryption Computations
di: Sefsaf, Bilel, et al.
Pubblicazione: (2026)

ByzFL: Research Framework for Robust Federated Learning
di: González, Marc, et al.
Pubblicazione: (2025)

BlazeFL: Fast and Deterministic Federated Learning Simulation
di: Azuma, Kitsuya, et al.
Pubblicazione: (2026)

Blending Imitation and Reinforcement Learning for Robust Policy Improvement
di: Liu, Xuefeng, et al.
Pubblicazione: (2023)

Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor
di: Yu, Hao, et al.
Pubblicazione: (2024)

SOFA-FL: Self-Organizing Hierarchical Federated Learning with Adaptive Clustered Data Sharing
di: Ni, Yi, et al.
Pubblicazione: (2025)

BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python
di: Haines, Nathaniel, et al.
Pubblicazione: (2024)

Continual Learning with Synthetic Boundary Experience Blending
di: Hsu, Chih-Fan, et al.
Pubblicazione: (2025)

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

Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning
di: Dou, Xuhui, et al.
Pubblicazione: (2026)

Learning and Blending Robot Hugging Behaviors in Time and Space
di: Drolet, Michael, et al.
Pubblicazione: (2022)

FL-PBM: Pre-Training Backdoor Mitigation for Federated Learning
di: Wehbi, Osama, et al.
Pubblicazione: (2026)

LiD-FL: Towards List-Decodable Federated Learning
di: Liu, Hong, et al.
Pubblicazione: (2024)

DynamicFL: Federated Learning with Dynamic Communication Resource Allocation
di: Le, Qi, et al.
Pubblicazione: (2024)

MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning
di: Zhang, Jianyi, et al.
Pubblicazione: (2024)

Uncertainty Quantification for Machine Learning in Healthcare: A Survey
di: López, L. Julián Lechuga, et al.
Pubblicazione: (2025)