Imagen de Portada

FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Song, Changlin, Saxena, Divya, Cao, Jiannong, Zhao, Yuqing
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data
por: Zhao, Yushan, et al.
Publicado: (2025)

FedAFD: Multimodal Federated Learning via Adversarial Fusion and Distillation
por: Tan, Min, et al.
Publicado: (2026)

Global Intervention and Distillation for Federated Out-of-Distribution Generalization
por: Qi, Zhuang, et al.
Publicado: (2025)

FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning
por: Kim, Seongyoon, et al.
Publicado: (2024)

Segment Any RGB-Thermal Model with Language-aided Distillation
por: Xing, Dong, et al.
Publicado: (2025)

FedBrain-Distill: Communication-Efficient Federated Brain Tumor Classification Using Ensemble Knowledge Distillation on Non-IID Data
por: Gohari, Rasoul Jafari, et al.
Publicado: (2024)

Flow-OPD: On-Policy Distillation for Flow Matching Models
por: Fang, Zhen, et al.
Publicado: (2026)

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

AdaptCL: Adaptive Continual Learning for Tackling Heterogeneity in Sequential Datasets
por: Zhao, Yuqing, et al.
Publicado: (2022)

Heterogeneous Generative Knowledge Distillation with Masked Image Modeling
por: Wang, Ziming, et al.
Publicado: (2023)

Adversarial Prompt Distillation for Vision-Language Models
por: Luo, Lin, et al.
Publicado: (2024)

Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data
por: Qiao, Yu, et al.
Publicado: (2024)

DisCa: Accelerating Video Diffusion Transformers with Distillation-Compatible Learnable Feature Caching
por: Zou, Chang, et al.
Publicado: (2026)

X-Distill: Cross-Architecture Vision Distillation for Visuomotor Learning
por: Shao, Maanping, et al.
Publicado: (2026)

CAPEEN: Image Captioning with Early Exits and Knowledge Distillation
por: Bajpai, Divya Jyoti, et al.
Publicado: (2024)

Inference-Time Diffusion Model Distillation
por: Park, Geon Yeong, et al.
Publicado: (2024)

Generative Dataset Distillation: Balancing Global Structure and Local Details
por: Li, Longzhen, et al.
Publicado: (2024)

FedGIN: Federated Learning with Dynamic Global Intensity Non-linear Augmentation for Organ Segmentation using Multi-modal Images
por: Nagaraju, Sachin Dudda, et al.
Publicado: (2025)

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models
por: Wang, Qichao, et al.
Publicado: (2026)

Score Distillation of Flow Matching Models
por: Zhou, Mingyuan, et al.
Publicado: (2025)

FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization
por: Yu, Xiaoyang, et al.
Publicado: (2025)

Continual Learning of Diffusion Models with Generative Distillation
por: Masip, Sergi, et al.
Publicado: (2023)

MorphDistill: Distilling Unified Morphological Knowledge from Pathology Foundation Models for Colorectal Cancer Survival Prediction
por: Khan, Hikmat, et al.
Publicado: (2026)

Generative Dataset Distillation Based on Diffusion Model
por: Su, Duo, et al.
Publicado: (2024)

Accelerating Diffusion Models with One-to-Many Knowledge Distillation
por: Zhang, Linfeng, et al.
Publicado: (2024)

AnimateDiff-Lightning: Cross-Model Diffusion Distillation
por: Lin, Shanchuan, et al.
Publicado: (2024)

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data
por: Chunduru, Abhijit, et al.
Publicado: (2025)

Dual-Model Distillation for Efficient Action Classification with Hybrid Edge-Cloud Solution
por: Wei, Timothy, et al.
Publicado: (2024)

FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models
por: Lin, Hui, et al.
Publicado: (2025)

AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation
por: Gu, Yuchao, et al.
Publicado: (2026)

FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
por: Hu, Chen, et al.
Publicado: (2024)

CompoDistill: Attention Distillation for Compositional Reasoning in Multimodal LLMs
por: Kim, Jiwan, et al.
Publicado: (2025)

From Structure to Detail: Hierarchical Distillation for Efficient Diffusion Model
por: Cheng, Hanbo, et al.
Publicado: (2025)

GVD: Guiding Video Diffusion Model for Scalable Video Distillation
por: Li, Kunyang, et al.
Publicado: (2025)

Distilling Multi-view Diffusion Models into 3D Generators
por: Qin, Hao, et al.
Publicado: (2025)

Enhancing Monocular 3D Scene Completion with Diffusion Model
por: Song, Changlin, et al.
Publicado: (2025)

Distilling Channels for Efficient Deep Tracking
por: Ge, Shiming, et al.
Publicado: (2024)

Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation
por: Zhu, Chunzheng, et al.
Publicado: (2026)

Learning to Project for Cross-Task Knowledge Distillation
por: Auty, Dylan, et al.
Publicado: (2024)

FDBPL: Faster Distillation-Based Prompt Learning for Region-Aware Vision-Language Models Adaptation
por: Zhang, Zherui, et al.
Publicado: (2025)