Copertina

Overcoming the Challenges of Batch Normalization in Federated Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Guerraoui, Rachid, Pinot, Rafael, Rizk, Geovani, Stephan, John, Taiani, François
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

ByzFL: Research Framework for Robust Federated Learning
di: González, Marc, et al.
Pubblicazione: (2025)

Adaptive Gradient Clipping for Robust Federated Learning
di: Allouah, Youssef, et al.
Pubblicazione: (2024)

Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
di: Allouah, Youssef, et al.
Pubblicazione: (2024)

Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
di: Allouah, Youssef, et al.
Pubblicazione: (2024)

On the Relevance of Byzantine Robust Optimization Against Data Poisoning
di: Farhadkhani, Sadegh, et al.
Pubblicazione: (2024)

Towards Trustworthy Federated Learning with Untrusted Participants
di: Allouah, Youssef, et al.
Pubblicazione: (2025)

Robust Federated Inference
di: Dhasade, Akash, et al.
Pubblicazione: (2025)

Revisiting Ensembling in One-Shot Federated Learning
di: Allouah, Youssef, et al.
Pubblicazione: (2024)

Balancing Privacy, Robustness, and Efficiency in Machine Learning
di: Allouah, Youssef, et al.
Pubblicazione: (2023)

Robust and Efficient Collaborative Learning
di: Mrini, Abdellah El, et al.
Pubblicazione: (2025)

Your Neighbors Know: Leveraging Local Neighborhoods for Backdoor Detection in Decentralized Learning
di: Biswas, Sayan, et al.
Pubblicazione: (2026)

Distributional Machine Unlearning via Selective Data Removal
di: Allouah, Youssef, et al.
Pubblicazione: (2025)

Making Batch Normalization Great in Federated Deep Learning
di: Zhong, Jike, et al.
Pubblicazione: (2023)

BN-SCAFFOLD: controlling the drift of Batch Normalization statistics in Federated Learning
di: Quintana, Gonzalo Iñaki, et al.
Pubblicazione: (2024)

Fairness Meets Privacy: Integrating Differential Privacy and Demographic Parity in Multi-class Classification
di: Say, Lilian, et al.
Pubblicazione: (2025)

Privacy Amplification by Missing Data
di: Roburin, Simon, et al.
Pubblicazione: (2026)

The Utility and Complexity of in- and out-of-Distribution Machine Unlearning
di: Allouah, Youssef, et al.
Pubblicazione: (2024)

Supervised Batch Normalization
di: Faye, Bilal, et al.
Pubblicazione: (2024)

Efficient Federated Search for Retrieval-Augmented Generation using Lightweight Routing
di: Dhasade, Akash, et al.
Pubblicazione: (2025)

FIRMA: FIbonacci Ring Model Aggregation for Privacy-preserving Federated Learning
di: Hedjam, Rachid
Pubblicazione: (2026)

Accelerating Transfer Learning with Near-Data Computation on Cloud Object Stores
di: Petrescu, Diana, et al.
Pubblicazione: (2022)

Certified Unlearning for Neural Networks
di: Koloskova, Anastasia, et al.
Pubblicazione: (2025)

Unified Privacy Guarantees for Decentralized Learning via Matrix Factorization
di: Bellet, Aurélien, et al.
Pubblicazione: (2025)

Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models
di: Verine, Alexandre, et al.
Pubblicazione: (2026)

Lévy-Flow Models: Heavy-Tail-Aware Normalizing Flows for Financial Risk Management
di: Drissi, Rachid
Pubblicazione: (2026)

Batch Normalization Decomposed
di: Nachum, Ido, et al.
Pubblicazione: (2024)

On the Inherent Anonymity of Gossiping
di: Guerraoui, Rachid, et al.
Pubblicazione: (2023)

Log Probability Tracking of LLM APIs
di: Chauvin, Timothée, et al.
Pubblicazione: (2025)

The Privacy Power of Correlated Noise in Decentralized Learning
di: Allouah, Youssef, et al.
Pubblicazione: (2024)

Under manipulations, are some AI models harder to audit?
di: Godinot, Augustin, et al.
Pubblicazione: (2024)

Batch Normalization for Neural Networks on Complex Domains
di: Nguyen, Xuan Son, et al.
Pubblicazione: (2026)

Impact of Batch Normalization on Convolutional Network Representations
di: Potgieter, Hermanus L., et al.
Pubblicazione: (2025)

Adaptive Deadline and Batch Layered Synchronized Federated Learning
di: Goren, Asaf, et al.
Pubblicazione: (2025)

Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
di: Palenicek, Daniel, et al.
Pubblicazione: (2025)

Mosaic Learning: A Framework for Decentralized Learning with Model Fragmentation
di: Biswas, Sayan, et al.
Pubblicazione: (2026)

Overcoming Challenges of Partial Client Participation in Federated Learning : A Comprehensive Review
di: Sen, Mrinmay, et al.
Pubblicazione: (2025)

PeerSwap: A Peer-Sampler with Randomness Guarantees
di: Guerraoui, Rachid, et al.
Pubblicazione: (2024)

Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning
di: Chen, Hongyao, et al.
Pubblicazione: (2025)

CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
di: Bhatt, Aditya, et al.
Pubblicazione: (2019)

Queries, Representation & Detection: The Next 100 Model Fingerprinting Schemes
di: Godinot, Augustin, et al.
Pubblicazione: (2024)