Decoding Federated Learning: The FedNAM+ Conformal Revolution
Fuente:
arXiv
Saved in:
| Main Authors: | Balija, Sree Bhargavi, Nanda, Amitash, Sahoo, Debashis |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FedNAMs: Performing Interpretability Analysis in Federated Learning Context
by: Nanda, Amitash, et al.
Published: (2025)
by: Nanda, Amitash, et al.
Published: (2025)
CPTQuant - A Novel Mixed Precision Post-Training Quantization Techniques for Large Language Models
by: Nanda, Amitash, et al.
Published: (2024)
by: Nanda, Amitash, et al.
Published: (2024)
FedMM-X: A Trustworthy and Interpretable Framework for Federated Multi-Modal Learning in Dynamic Environments
by: Balija, Sree Bhargavi
Published: (2025)
by: Balija, Sree Bhargavi
Published: (2025)
FedCVU: Federated Learning for Cross-View Video Understanding
by: Zhang, Shenghan, et al.
Published: (2026)
by: Zhang, Shenghan, et al.
Published: (2026)
FedQuad: Federated Stochastic Quadruplet Learning to Mitigate Data Heterogeneity
by: Goksu, Ozgu, et al.
Published: (2025)
by: Goksu, Ozgu, 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)
FedMGP: Personalized Federated Learning with Multi-Group Text-Visual Prompts
by: Bo, Weihao, et al.
Published: (2025)
by: Bo, Weihao, et al.
Published: (2025)
FedHCA$^2$: Towards Hetero-Client Federated Multi-Task Learning
by: Lu, Yuxiang, et al.
Published: (2023)
by: Lu, Yuxiang, et al.
Published: (2023)
FedStyle: Style-Based Federated Learning Crowdsourcing Framework for Art Commissions
by: Ran, Changjuan, et al.
Published: (2024)
by: Ran, Changjuan, et al.
Published: (2024)
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)
FedCTTA: A Collaborative Approach to Continual Test-Time Adaptation in Federated Learning
by: Rajib, Rakibul Hasan, et al.
Published: (2025)
by: Rajib, Rakibul Hasan, et al.
Published: (2025)
WarmFed: Federated Learning with Warm-Start for Globalization and Personalization Via Personalized Diffusion Models
by: Feng, Tao, et al.
Published: (2025)
by: Feng, Tao, et al.
Published: (2025)
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)
FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging
by: Sahoo, Pranab, et al.
Published: (2024)
by: Sahoo, Pranab, 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)
FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
by: Zheng, Weiying, et al.
Published: (2025)
by: Zheng, Weiying, et al.
Published: (2025)
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning
by: Lee, Gihun, et al.
Published: (2023)
by: Lee, Gihun, 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)
FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning
by: Devkota, Alina, et al.
Published: (2026)
by: Devkota, Alina, et al.
Published: (2026)
Intracranial Hemorrhage Detection Using Neural Network Based Methods With Federated Learning
by: Srivastava, Utkarsh Chandra, et al.
Published: (2020)
by: Srivastava, Utkarsh Chandra, et al.
Published: (2020)
FedAFD: Multimodal Federated Learning via Adversarial Fusion and Distillation
by: Tan, Min, et al.
Published: (2026)
by: Tan, Min, et al.
Published: (2026)
FedPromo: Federated Lightweight Proxy Models at the Edge Bring New Domains to Foundation Models
by: Caligiuri, Matteo, et al.
Published: (2025)
by: Caligiuri, Matteo, et al.
Published: (2025)
FedPURIN: Programmed Update and Reduced INformation for Sparse Personalized Federated Learning
by: Xie, Lunchen, et al.
Published: (2025)
by: Xie, Lunchen, et al.
Published: (2025)
FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data
by: Xu, Binqian, et al.
Published: (2024)
by: Xu, Binqian, et al.
Published: (2024)
pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2025)
by: Ghiasvand, Sajjad, et al.
Published: (2025)
Cyclic Sparse Training: Is it Enough?
by: Gadhikar, Advait, et al.
Published: (2024)
by: Gadhikar, Advait, et al.
Published: (2024)
FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification
by: Yu, Po-Hsien, et al.
Published: (2025)
by: Yu, Po-Hsien, et al.
Published: (2025)
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)
FedAli: Personalized Federated Learning Alignment with Prototype Layers for Generalized Mobile Services
by: Ek, Sannara, et al.
Published: (2024)
by: Ek, Sannara, et al.
Published: (2024)
FedDiff: Diffusion Model Driven Federated Learning for Multi-Modal and Multi-Clients
by: Li, DaiXun, et al.
Published: (2023)
by: Li, DaiXun, et al.
Published: (2023)
FedCAR: Cross-client Adaptive Re-weighting for Generative Models in Federated Learning
by: Kim, Minjun, et al.
Published: (2024)
by: Kim, Minjun, et al.
Published: (2024)
FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning
by: Lau, Kin Wai, et al.
Published: (2024)
by: Lau, Kin Wai, et al.
Published: (2024)
Learning Conformal Explainers for Image Classifiers
by: Alkhatib, Amr, et al.
Published: (2025)
by: Alkhatib, Amr, et al.
Published: (2025)
Conformal Cross-Modal Active Learning
by: Nguyen, Huy Hoang, et al.
Published: (2026)
by: Nguyen, Huy Hoang, et al.
Published: (2026)
FedDefender: Backdoor Attack Defense in Federated Learning
by: Gill, Waris, et al.
Published: (2023)
by: Gill, Waris, et al.
Published: (2023)
pFedBBN: A Personalized Federated Test-Time Adaptation with Balanced Batch Normalization for Class-Imbalanced Data
by: Iftee, Md Akil Raihan, et al.
Published: (2025)
by: Iftee, Md Akil Raihan, et al.
Published: (2025)
FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
by: Kim, Seung-Wook, et al.
Published: (2025)
by: Kim, Seung-Wook, et al.
Published: (2025)
Conformal-in-the-Loop for Learning with Imbalanced Noisy Data
by: Graham-Knight, John Brandon, et al.
Published: (2024)
by: Graham-Knight, John Brandon, et al.
Published: (2024)
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise
by: Wu, Nannan, et al.
Published: (2023)
by: Wu, Nannan, et al.
Published: (2023)
Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
by: Kirchner, Max, et al.
Published: (2025)
by: Kirchner, Max, et al.
Published: (2025)
Similar Items
-
FedNAMs: Performing Interpretability Analysis in Federated Learning Context
by: Nanda, Amitash, et al.
Published: (2025) -
CPTQuant - A Novel Mixed Precision Post-Training Quantization Techniques for Large Language Models
by: Nanda, Amitash, et al.
Published: (2024) -
FedMM-X: A Trustworthy and Interpretable Framework for Federated Multi-Modal Learning in Dynamic Environments
by: Balija, Sree Bhargavi
Published: (2025) -
FedCVU: Federated Learning for Cross-View Video Understanding
by: Zhang, Shenghan, et al.
Published: (2026) -
FedQuad: Federated Stochastic Quadruplet Learning to Mitigate Data Heterogeneity
by: Goksu, Ozgu, et al.
Published: (2025)