Imagen de Portada

Asynchronous Probability Ensembling for Federated Disaster Detection

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Martins, Emanuel Teixeira, Moreira, Rodrigo, Moreira, Larissa Ferreira Rodrigues, Villaça, Rodolfo S., Neto, Augusto, Silva, Flávio de Oliveira
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

TRACE: Traceroute-based Internet Route change Analysis with Ensemble Learning
por: Suzuki, Raul, et al.
Publicado: (2026)

Evaluating the Potential of Federated Learning for Maize Leaf Disease Prediction
por: Antico, Thalita Mendonça, et al.
Publicado: (2024)

Evaluating Temporal and Structural Anomaly Detection Paradigms for DDoS Traffic
por: Lima, Yasmin Souza, et al.
Publicado: (2026)

Generalizable Hyperparameter Optimization for Federated Learning on Non-IID Cancer Images
por: Ribeiro, Elisa Gonçalves, et al.
Publicado: (2026)

An Intelligent Native Network Slicing Security Architecture Empowered by Federated Learning
por: Moreira, Rodrigo, et al.
Publicado: (2024)

Exploiting Test-Time Augmentation in Federated Learning for Brain Tumor MRI Classification
por: Melo, Thamara Leandra de Deus, et al.
Publicado: (2026)

VINEVI: A Virtualized Network Vision Architecture for Smart Monitoring of Heterogeneous Applications and Infrastructures
por: Moreira, Rodrigo, et al.
Publicado: (2024)

Improving Sickle Cell Disease Classification: A Fusion of Conventional Classifiers, Segmented Images, and Convolutional Neural Networks
por: Cardoso, Victor Júnio Alcântara, et al.
Publicado: (2024)

Data Augmentation and Convolutional Network Architecture Influence on Distributed Learning
por: Jansen, Victor Forattini, et al.
Publicado: (2026)

Energy-Aware Ensemble Learning for Coffee Leaf Disease Classification
por: Moreira, Larissa Ferreira Rodrigues, et al.
Publicado: (2026)

Performance Evaluation and Threat Mitigation in Large-scale 5G Core Deployment
por: Moreira, Rodrigo, et al.
Publicado: (2025)

FedPAE: Peer-Adaptive Ensemble Learning for Asynchronous and Model-Heterogeneous Federated Learning
por: Mueller, Brianna, et al.
Publicado: (2024)

AI-driven Orchestration at Scale: Estimating Service Metrics on National-Wide Testbeds
por: Moreira, Rodrigo, et al.
Publicado: (2025)

AGORA: Agentic Green Orchestration Architecture for Beyond 5G Networks
por: Moreira, Rodrigo, et al.
Publicado: (2026)

An Intelligent eUPF for Time-Sensitive Path Selection in B5G Edge Networks
por: Moreira, Rodrigo, et al.
Publicado: (2026)

Noisy Neighbor Influence in the Data Plane of Beyond 5G Networks
por: Moreira, Rodrigo, et al.
Publicado: (2026)

Towards a Systematic Approach to Design New Ensemble Learning Algorithms
por: Mendes-Moreira, João, et al.
Publicado: (2024)

Optimizing Edge Gaming Slices through an Enhanced User Plane Function and Analytics in Beyond-5G Networks
por: da Silva, Bruno Marques, et al.
Publicado: (2025)

Towards Sustainability in 6G Network Slicing with Energy-Saving and Optimization Methods
por: Moreira, Rodrigo, et al.
Publicado: (2025)

Intelligent Data-Driven Architectural Features Orchestration for Network Slicing
por: Moreira, Rodrigo, et al.
Publicado: (2024)

Pure Exploration in Asynchronous Federated Bandits
por: Wang, Zichen, et al.
Publicado: (2023)

Improving the network traffic classification using the Packet Vision approach
por: Moreira, Rodrigo, et al.
Publicado: (2024)

Momentum Approximation in Asynchronous Private Federated Learning
por: Yu, Tao, et al.
Publicado: (2024)

Aggregation on Learnable Manifolds for Asynchronous Federated Optimization
por: Licudi, Archie, et al.
Publicado: (2025)

An Ensembled Penalized Federated Learning Framework for Falling People Detection
por: Rao, Sizhe, et al.
Publicado: (2025)

Resource Allocation Influence on Application Performance in Sliced Testbeds
por: Moreira, Rodrigo, et al.
Publicado: (2024)

Towards Cognitive Service Delivery on B5G through AIaaS Architecture
por: Moreira, Larissa F. Rodrigues, et al.
Publicado: (2024)

Enhancing Robustness of Asynchronous EEG-Based Movement Prediction using Classifier Ensembles
por: Kueper, Niklas, et al.
Publicado: (2026)

Asynchronous Federated Unlearning with Invariance Calibration for Medical Imaging
por: Cai, Zhaoyuan, et al.
Publicado: (2026)

Mobility-Aware Asynchronous Federated Learning with Dynamic Sparsification
por: Yan, Jintao, et al.
Publicado: (2025)

DriftGuard: Mitigating Asynchronous Data Drift in Federated Learning
por: Han, Yizhou, et al.
Publicado: (2026)

Scalable Asynchronous Federated Modeling for Spatial Data
por: Shi, Jianwei, et al.
Publicado: (2025)

Enhancing PTSD Outcome Prediction with Ensemble Models in Disaster Contexts
por: Siddiqua, Ayesha, et al.
Publicado: (2024)

FAuNO: Semi-Asynchronous Federated Reinforcement Learning Framework for Task Offloading in Edge Systems
por: Metelo, Frederico, et al.
Publicado: (2025)

Orthogonal Calibration for Asynchronous Federated Learning
por: Zhang, Jiayun, et al.
Publicado: (2025)

bde: A Python Package for Bayesian Deep Ensembles via MILE
por: Arvanitis, Vyron, et al.
Publicado: (2026)

Mitigating System Bias in Resource Constrained Asynchronous Federated Learning Systems
por: Gao, Jikun, et al.
Publicado: (2024)

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

Kernel-Based Ensemble Gaussian Mixture Probability Hypothesis Density Filter
por: Durant, Dalton, et al.
Publicado: (2025)

Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
por: Chang, Xiangyu, et al.
Publicado: (2025)