Image de couverture de livre

Federated Impression for Learning with Distributed Heterogeneous Data

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Arya, Atrin, Ayromlou, Sana, Saadat, Armin, Abolmaesumi, Purang, Li, Xiaoxiao
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition 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

CCSI: Continual Class-Specific Impression for Data-free Class Incremental Learning
par: Ayromlou, Sana, et autres
Publié: (2024)

FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging
par: Sahoo, Pranab, et autres
Publié: (2024)

FedDUAL: A Dual-Strategy with Adaptive Loss and Dynamic Aggregation for Mitigating Data Heterogeneity in Federated Learning
par: Sahoo, Pranab, et autres
Publié: (2024)

Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration
par: Morafah, Mahdi, et autres
Publié: (2024)

Local Performance vs. Out-of-Distribution Generalization: An Empirical Analysis of Personalized Federated Learning in Heterogeneous Data Environments
par: Hussaini, Mortesa, et autres
Publié: (2025)

Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy
par: Ukaye, Asim, et autres
Publié: (2026)

Task-Agnostic Federated Learning
par: Yao, Zhengtao, et autres
Publié: (2024)

Flashback: Understanding and Mitigating Forgetting in Federated Learning
par: Aljahdali, Mohammed, et autres
Publié: (2024)

Federated Learning Client Pruning for Noisy Labels
par: Morafah, Mahdi, et autres
Publié: (2024)

FedWon: Triumphing Multi-domain Federated Learning Without Normalization
par: Zhuang, Weiming, et autres
Publié: (2023)

FeDMRA: Federated Incremental Learning with Dynamic Memory Replay Allocation
par: Wang, Tiantian, et autres
Publié: (2026)

Caching Techniques for Reducing the Communication Cost of Federated Learning in IoT Environments
par: Alhonainy, Ahmad, et autres
Publié: (2025)

Training Together, Diagnosing Better: Federated Learning for Collagen VI-Related Dystrophies
par: Brull, Astrid, et autres
Publié: (2025)

FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning
par: Kim, Seongyoon, et autres
Publié: (2024)

FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields
par: Yun, Junhyeog, et autres
Publié: (2025)

FAST: Federated Active Learning with Foundation Models for Communication-efficient Sampling and Training
par: Li, Haoyuan, et autres
Publié: (2025)

Navigating Data Heterogeneity in Federated Learning A Semi-Supervised Federated Object Detection
par: Kim, Taehyeon, et autres
Publié: (2023)

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data
par: Chunduru, Abhijit, et autres
Publié: (2025)

Flexible Communication for Optimal Distributed Learning over Unpredictable Networks
par: Tyagi, Sahil, et autres
Publié: (2023)

Recurrent Early Exits for Federated Learning with Heterogeneous Clients
par: Lee, Royson, et autres
Publié: (2024)

Parallax: Runtime Parallelization for Operator Fallbacks in Heterogeneous Edge Systems
par: Tang, Chong, et autres
Publié: (2025)

Spatial-Temporal Federated Learning for Lifelong Person Re-identification on Distributed Edges
par: Zhang, Lei, et autres
Publié: (2022)

PointSplit: Towards On-device 3D Object Detection with Heterogeneous Low-power Accelerators
par: Park, Keondo, et autres
Publié: (2025)

FedDM: Enhancing Communication Efficiency and Handling Data Heterogeneity in Federated Diffusion Models
par: Vora, Jayneel, et autres
Publié: (2024)

ARIA: On the Interaction Between Architectures, Initialization and Aggregation Methods for Federated Visual Classification
par: Siomos, Vasilis, et autres
Publié: (2023)

Distributed Hybrid Parallelism for Large Language Models: Comparative Study and System Design Guide
par: Amer, Hossam, et autres
Publié: (2026)

LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models
par: Chang, Tzu-Tao, et autres
Publié: (2025)

CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training
par: Karim, Rezaul, et autres
Publié: (2026)

A Closer Look at Personalized Fine-Tuning in Heterogeneous Federated Learning
par: Chen, Minghui, et autres
Publié: (2025)

Fed-EC: Bandwidth-Efficient Clustering-Based Federated Learning For Autonomous Visual Robot Navigation
par: Gummadi, Shreya, et autres
Publié: (2024)

FedMM: Federated Multi-Modal Learning with Modality Heterogeneity in Computational Pathology
par: Peng, Yuanzhe, et autres
Publié: (2024)

Investigation of Federated Learning Algorithms for Retinal Optical Coherence Tomography Image Classification with Statistical Heterogeneity
par: Amgain, Sanskar, et autres
Publié: (2024)

Validation of Various Normalization Methods for Brain Tumor Segmentation: Can Federated Learning Overcome This Heterogeneity?
par: Fiszer, Jan, et autres
Publié: (2025)

RE-POSE: Synergizing Reinforcement Learning-Based Partitioning and Offloading for Edge Object Detection
par: Shi, Jianrui, et autres
Publié: (2025)

Beyond Corner Patches: Semantics-Aware Backdoor Attack in Federated Learning
par: Herath, Kavindu, et autres
Publié: (2026)

Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory
par: Wang, Naibo, et autres
Publié: (2024)

Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout
par: Liu, Ji, et autres
Publié: (2025)

TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance
par: Gill, Waris, et autres
Publié: (2023)

FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels
par: Gholami, Sina, et autres
Publié: (2026)

Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation
par: He, Xiaoxiao, et autres
Publié: (2025)