Copertina

Capture Global Feature Statistics for One-Shot Federated Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Guan, Zenghao, Zhou, Yucan, Gu, Xiaoyan
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Enhancing Federated Class-Incremental Learning via Spatial-Temporal Statistics Aggregation
di: Guan, Zenghao, et al.
Pubblicazione: (2025)

The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics
di: Turazza, Fabio, et al.
Pubblicazione: (2026)

One-Shot Clustering for Federated Learning
di: Zuziak, Maciej Krzysztof, et al.
Pubblicazione: (2025)

One-Shot Clustering for Federated Learning Under Clustering-Agnostic Assumption
di: Zuziak, Maciej Krzysztof, et al.
Pubblicazione: (2025)

Parametric Feature Transfer: One-shot Federated Learning with Foundation Models
di: Beitollahi, Mahdi, et al.
Pubblicazione: (2024)

FederatedFactory: Generative One-Shot Learning for Extremely Non-IID Distributed Scenarios
di: Moleri, Andrea, et al.
Pubblicazione: (2026)

Decoupled Federated Learning on Long-Tailed and Non-IID data with Feature Statistics
di: Chen, Zhuoxin, et al.
Pubblicazione: (2024)

Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models
di: Ye, Wenxuan, et al.
Pubblicazione: (2025)

One-Shot Federated Learning with Bayesian Pseudocoresets
di: d'Hondt, Tim, et al.
Pubblicazione: (2024)

Multi-Modal One-Shot Federated Ensemble Learning for Medical Data with Vision Large Language Model
di: Wang, Naibo, et al.
Pubblicazione: (2025)

Semi-Supervised One-Shot Imitation Learning
di: Wu, Philipp, et al.
Pubblicazione: (2024)

FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning
di: Ma, Evelyn, et al.
Pubblicazione: (2024)

Capturing Individual Human Preferences with Reward Features
di: Barreto, André, et al.
Pubblicazione: (2025)

Feature-Space Generative Models for One-Shot Class-Incremental Learning
di: Foster, Jack, et al.
Pubblicazione: (2026)

Federated Learning with Multi-Partner OneFlorida+ Consortium Data for Predicting Major Postoperative Complications
di: Ren, Yuanfang, et al.
Pubblicazione: (2026)

FedMP: Tackling Medical Feature Heterogeneity in Federated Learning from a Manifold Perspective
di: Zhou, Zhekai, et al.
Pubblicazione: (2025)

Is Meta-Learning Out? Rethinking Unsupervised Few-Shot Classification with Limited Entropy
di: Guan, Yunchuan, et al.
Pubblicazione: (2025)

Unlearning Clients, Features and Samples in Vertical Federated Learning
di: Varshney, Ayush K., et al.
Pubblicazione: (2025)

Personalized Federated Learning via Feature Distribution Adaptation
di: Mclaughlin, Connor J., et al.
Pubblicazione: (2024)

One-Shot Imitation Learning with Invariance Matching for Robotic Manipulation
di: Zhang, Xinyu, et al.
Pubblicazione: (2024)

One-shot Federated Learning Methods: A Practical Guide
di: Liu, Xiang, et al.
Pubblicazione: (2025)

CAOS: Conformal Aggregation of One-Shot Predictors
di: Waldron, Maja
Pubblicazione: (2026)

Federated Few-Shot Learning for Epileptic Seizure Detection Under Privacy Constraints
di: Sysoykova, Ekaterina, et al.
Pubblicazione: (2025)

Selector-Guided Autonomous Curriculum for One-Shot Reinforcement Learning from Verifiable Rewards
di: Dave, Rudray, et al.
Pubblicazione: (2026)

FedEGG: Federated Learning with Explicit Global Guidance
di: Zhai, Kun, et al.
Pubblicazione: (2024)

Feature Distillation is the Better Choice for Model-Heterogeneous Federated Learning
di: Li, Yichen, et al.
Pubblicazione: (2025)

Projecting Out the Malice: A Global Subspace Approach to LLM Detoxification
di: Duan, Zenghao, et al.
Pubblicazione: (2026)

The Weight Gram Matrix Captures Sequential Feature Linearization in Deep Networks
di: Cha, Taehun, et al.
Pubblicazione: (2026)

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
di: Auddy, Arnab, et al.
Pubblicazione: (2026)

FedNSAM:Consistency of Local and Global Flatness for Federated Learning
di: Liu, Junkang, et al.
Pubblicazione: (2026)

FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices
di: Yao, Dezhong, et al.
Pubblicazione: (2025)

A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
di: Yan, Yunlu, et al.
Pubblicazione: (2023)

Enhancing AI Assisted Writing with One-Shot Implicit Negative Feedback
di: Towle, Benjamin, et al.
Pubblicazione: (2024)

Privacy-Preserving Personalized Federated Learning for Distributed Photovoltaic Disaggregation under Statistical Heterogeneity
di: Chen, Xiaolu, et al.
Pubblicazione: (2025)

Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches
di: Li, Siqi, et al.
Pubblicazione: (2023)

FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
di: Liu, Xiang, et al.
Pubblicazione: (2023)

SymDrift: One-Shot Generative Modeling under Symmetries
di: Darouich, Samir, et al.
Pubblicazione: (2026)

One-Shot Domain Incremental Learning
di: Esaki, Yasushi, et al.
Pubblicazione: (2024)

Local-Global Feature Fusion for Subject-Independent EEG Emotion Recognition
di: Zhou, Zheng, et al.
Pubblicazione: (2026)

Global Outlier Detection in a Federated Learning Setting with Isolation Forest
di: Malpetti, Daniele, et al.
Pubblicazione: (2024)