Adaptive Dual-Mode Distillation with Incentive Schemes for Scalable, Heterogeneous Federated Learning on Non-IID Data
Fuente:
arXiv
Saved in:
| Main Author: | Iqbal, Zahid |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data
by: Zhao, Yushan, et al.
Published: (2025)
by: Zhao, Yushan, et al.
Published: (2025)
Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy
by: Ardıç, Emre, et al.
Published: (2026)
by: Ardıç, Emre, et al.
Published: (2026)
Sample Selection Using Multi-Task Autoencoders in Federated Learning with Non-IID Data
by: Ardıç, Emre, et al.
Published: (2026)
by: Ardıç, Emre, et al.
Published: (2026)
FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning
by: Song, Changlin, et al.
Published: (2024)
by: Song, Changlin, et al.
Published: (2024)
FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework
by: He, Yuchen, et al.
Published: (2024)
by: He, Yuchen, et al.
Published: (2024)
Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data
by: Qiao, Yu, et al.
Published: (2024)
by: Qiao, Yu, et al.
Published: (2024)
Generalizable Hyperparameter Optimization for Federated Learning on Non-IID Cancer Images
by: Ribeiro, Elisa Gonçalves, et al.
Published: (2026)
by: Ribeiro, Elisa Gonçalves, et al.
Published: (2026)
Studying Various Activation Functions and Non-IID Data for Machine Learning Model Robustness
by: Dang, Long, et al.
Published: (2025)
by: Dang, Long, et al.
Published: (2025)
One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity
by: Wang, Naibo, et al.
Published: (2024)
by: Wang, Naibo, et al.
Published: (2024)
Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions
by: Borazjani, Kasra, et al.
Published: (2025)
by: Borazjani, Kasra, et al.
Published: (2025)
FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning and Logit Distillation
by: Ma, Yuting, et al.
Published: (2024)
by: Ma, Yuting, et al.
Published: (2024)
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data
by: Sun, Yuxia, et al.
Published: (2025)
by: Sun, Yuxia, et al.
Published: (2025)
An Aggregation-Free Federated Learning for Tackling Data Heterogeneity
by: Wang, Yuan, et al.
Published: (2024)
by: Wang, Yuan, et al.
Published: (2024)
Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data
by: Chunduru, Abhijit, et al.
Published: (2025)
by: Chunduru, Abhijit, et al.
Published: (2025)
FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
by: Hu, Chen, et al.
Published: (2024)
by: Hu, Chen, et al.
Published: (2024)
FedQuad: Federated Stochastic Quadruplet Learning to Mitigate Data Heterogeneity
by: Goksu, Ozgu, et al.
Published: (2025)
by: Goksu, Ozgu, et al.
Published: (2025)
One-shot Federated Learning via Synthetic Distiller-Distillate Communication
by: Zhang, Junyuan, et al.
Published: (2024)
by: Zhang, Junyuan, et al.
Published: (2024)
Dual-granularity Sinkhorn Distillation for Enhanced Learning from Long-tailed Noisy Data
by: Hong, Feng, et al.
Published: (2025)
by: Hong, Feng, et al.
Published: (2025)
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
by: Wang, Lei, et al.
Published: (2024)
by: Wang, Lei, et al.
Published: (2024)
Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition
by: Guo, Guangyu, et al.
Published: (2021)
by: Guo, Guangyu, et al.
Published: (2021)
An Architecture Built for Federated Learning: Addressing Data Heterogeneity through Adaptive Normalization-Free Feature Recalibration
by: Siomos, Vasilis, et al.
Published: (2024)
by: Siomos, Vasilis, et al.
Published: (2024)
SelfFed: Self-Supervised Federated Learning for Data Heterogeneity and Label Scarcity in Medical Images
by: Khowaja, Sunder Ali, et al.
Published: (2023)
by: Khowaja, Sunder Ali, et al.
Published: (2023)
FedDUAL: A Dual-Strategy with Adaptive Loss and Dynamic Aggregation for Mitigating Data Heterogeneity in Federated Learning
by: Sahoo, Pranab, et al.
Published: (2024)
by: Sahoo, Pranab, et al.
Published: (2024)
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets
by: Gu, Xulin, et al.
Published: (2025)
by: Gu, Xulin, et al.
Published: (2025)
Data-to-Model Distillation: Data-Efficient Learning Framework
by: Sajedi, Ahmad, et al.
Published: (2024)
by: Sajedi, Ahmad, et al.
Published: (2024)
Is Exchangeability better than I.I.D to handle Data Distribution Shifts while Pooling Data for Data-scarce Medical image segmentation?
by: Roy, Ayush, et al.
Published: (2025)
by: Roy, Ayush, et al.
Published: (2025)
Adaptive Dual-Teacher Distillation with Subnetwork Rectification for Bridging Semantic Gaps in Black-Box Domain Adaptation
by: Zhang, Zhe, et al.
Published: (2026)
by: Zhang, Zhe, et al.
Published: (2026)
ZeroFlow: Scalable Scene Flow via Distillation
by: Vedder, Kyle, et al.
Published: (2023)
by: Vedder, Kyle, et al.
Published: (2023)
FedBrain-Distill: Communication-Efficient Federated Brain Tumor Classification Using Ensemble Knowledge Distillation on Non-IID Data
by: Gohari, Rasoul Jafari, et al.
Published: (2024)
by: Gohari, Rasoul Jafari, et al.
Published: (2024)
Distilling Knowledge from Heterogeneous Architectures for Semantic Segmentation
by: Huang, Yanglin, et al.
Published: (2025)
by: Huang, Yanglin, et al.
Published: (2025)
FedHENet: A Frugal Federated Learning Framework for Heterogeneous Environments
by: Dopico-Castro, Alejandro, et al.
Published: (2026)
by: Dopico-Castro, Alejandro, et al.
Published: (2026)
Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search
by: Yu, Sixing, et al.
Published: (2022)
by: Yu, Sixing, et al.
Published: (2022)
Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object Detection
by: Khalil, Ahmad, et al.
Published: (2024)
by: Khalil, Ahmad, et al.
Published: (2024)
Federated Learning with Label-Masking Distillation
by: Lu, Jianghu, et al.
Published: (2024)
by: Lu, Jianghu, et al.
Published: (2024)
Towards Robust Federated Learning via Logits Calibration on Non-IID Data
by: Qiao, Yu, et al.
Published: (2024)
by: Qiao, Yu, et al.
Published: (2024)
Taming Mode Collapse in Score Distillation for Text-to-3D Generation
by: Wang, Peihao, et al.
Published: (2023)
by: Wang, Peihao, et al.
Published: (2023)
A Data-Free Analytical Quantization Scheme for Deep Learning Models
by: Luqman, Ahmed, et al.
Published: (2024)
by: Luqman, Ahmed, et al.
Published: (2024)
One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
by: Yang, Mingzhao, et al.
Published: (2023)
by: Yang, Mingzhao, et al.
Published: (2023)
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
by: Su, Shangchao, et al.
Published: (2022)
by: Su, Shangchao, et al.
Published: (2022)
Adaptive Teaching with Shared Classifier for Knowledge Distillation
by: Jang, Jaeyeon, et al.
Published: (2024)
by: Jang, Jaeyeon, et al.
Published: (2024)
Similar Items
-
FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data
by: Zhao, Yushan, et al.
Published: (2025) -
Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy
by: Ardıç, Emre, et al.
Published: (2026) -
Sample Selection Using Multi-Task Autoencoders in Federated Learning with Non-IID Data
by: Ardıç, Emre, et al.
Published: (2026) -
FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning
by: Song, Changlin, et al.
Published: (2024) -
FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework
by: He, Yuchen, et al.
Published: (2024)