:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Goksu, Ozgu, Pugeault, Nicolas
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Computer Vision and Pattern Recognition
Accès en ligne:	https://arxiv.org/abs/2509.04107
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Enhancing Federated Quadruplet Learning: Stochastic Client Selection and Embedding Stability Analysis
par: Goksu, Ozgu, et autres
Publié: (2026)

Hybrid-Regularized Magnitude Pruning for Robust Federated Learning under Covariate Shift
par: Goksu, Ozgu, et autres
Publié: (2024)

The Bad Batches: Enhancing Self-Supervised Learning in Image Classification Through Representative Batch Curation
par: Goksu, Ozgu, et autres
Publié: (2024)

SelfFed: Self-Supervised Federated Learning for Data Heterogeneity and Label Scarcity in Medical Images
par: Khowaja, Sunder Ali, et autres
Publié: (2023)

FedHENet: A Frugal Federated Learning Framework for Heterogeneous Environments
par: Dopico-Castro, Alejandro, et autres
Publié: (2026)

FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data
par: Sun, Yuxia, et autres
Publié: (2025)

FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data
par: Xu, Binqian, et autres
Publié: (2024)

FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning and Logit Distillation
par: Ma, Yuting, 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)

Mitigating Group Bias in Federated Learning for Heterogeneous Devices
par: Selialia, Khotso, et autres
Publié: (2023)

An Aggregation-Free Federated Learning for Tackling Data Heterogeneity
par: Wang, Yuan, et autres
Publié: (2024)

Decoding Federated Learning: The FedNAM+ Conformal Revolution
par: Balija, Sree Bhargavi, et autres
Publié: (2025)

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

FedCVU: Federated Learning for Cross-View Video Understanding
par: Zhang, Shenghan, et autres
Publié: (2026)

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

FedMGP: Personalized Federated Learning with Multi-Group Text-Visual Prompts
par: Bo, Weihao, et autres
Publié: (2025)

FedHCA$^2$: Towards Hetero-Client Federated Multi-Task Learning
par: Lu, Yuxiang, et autres
Publié: (2023)

FedStyle: Style-Based Federated Learning Crowdsourcing Framework for Art Commissions
par: Ran, Changjuan, et autres
Publié: (2024)

FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise
par: Wu, Nannan, et autres
Publié: (2023)

Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
par: Wang, Lei, et autres
Publié: (2024)

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data
par: Zhao, Yushan, et autres
Publié: (2025)

FedCTTA: A Collaborative Approach to Continual Test-Time Adaptation in Federated Learning
par: Rajib, Rakibul Hasan, et autres
Publié: (2025)

FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models
par: Chen, Haokun, et autres
Publié: (2024)

WarmFed: Federated Learning with Warm-Start for Globalization and Personalization Via Personalized Diffusion Models
par: Feng, Tao, et autres
Publié: (2025)

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning
par: Lee, Gihun, et autres
Publié: (2023)

FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning
par: Devkota, Alina, et autres
Publié: (2026)

Adaptive Dual-Mode Distillation with Incentive Schemes for Scalable, Heterogeneous Federated Learning on Non-IID Data
par: Iqbal, Zahid
Publié: (2025)

FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
par: Zheng, Weiying, et autres
Publié: (2025)

Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object Detection
par: Khalil, Ahmad, et autres
Publié: (2024)

pFedBBN: A Personalized Federated Test-Time Adaptation with Balanced Batch Normalization for Class-Imbalanced Data
par: Iftee, Md Akil Raihan, et autres
Publié: (2025)

FedAFD: Multimodal Federated Learning via Adversarial Fusion and Distillation
par: Tan, Min, et autres
Publié: (2026)

Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search
par: Yu, Sixing, et autres
Publié: (2022)

UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks
par: Hassani, Atefe, et autres
Publié: (2024)

FedPURIN: Programmed Update and Reduced INformation for Sparse Personalized Federated Learning
par: Xie, Lunchen, et autres
Publié: (2025)

Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
par: Kirchner, Max, et autres
Publié: (2025)

One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
par: Yang, Mingzhao, et autres
Publié: (2023)

Federated Impression for Learning with Distributed Heterogeneous Data
par: Arya, Atrin, et autres
Publié: (2024)

FedDefender: Backdoor Attack Defense in Federated Learning
par: Gill, Waris, et autres
Publié: (2023)

FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning
par: Lau, Kin Wai, et autres
Publié: (2024)

Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor
par: Yu, Hao, et autres
Publié: (2024)