Copertina

Revisiting Ensembling in One-Shot Federated Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Allouah, Youssef, Dhasade, Akash, Guerraoui, Rachid, Gupta, Nirupam, Kermarrec, Anne-Marie, Pinot, Rafael, Pires, Rafael, Sharma, Rishi
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Decentralized Learning Made Easy with DecentralizePy
di: Dhasade, Akash, et al.
Pubblicazione: (2023)

Boosting Resource-Constrained Federated Learning Systems with Guessed Updates
di: Boukhari, Mohamed Yassine, et al.
Pubblicazione: (2021)

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

Get More for Less in Decentralized Learning Systems
di: Dhasade, Akash, et al.
Pubblicazione: (2023)

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

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

Practical Federated Learning without a Server
di: Dhasade, Akash, et al.
Pubblicazione: (2025)

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

Harnessing Increased Client Participation with Cohort-Parallel Federated Learning
di: Dhasade, Akash, et al.
Pubblicazione: (2024)

Decentralized Learning Made Practical with Client Sampling
di: de Vos, Martijn, et al.
Pubblicazione: (2023)

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

Energy-Aware Decentralized Learning with Intermittent Model Training
di: Dhasade, Akash, et al.
Pubblicazione: (2024)

Byzantine-Robust and Communication-Efficient Distributed Training: Compressive and Cyclic Gradient Coding
di: Li, Chengxi, et al.
Pubblicazione: (2026)

HarMoEny: Efficient Multi-GPU Inference of MoE Models
di: Doucet, Zachary, et al.
Pubblicazione: (2025)

Boosting Asynchronous Decentralized Learning with Model Fragmentation
di: Biswas, Sayan, et al.
Pubblicazione: (2024)

Efficient Pyramidal Analysis of Gigapixel Images on a Decentralized Modest Computer Cluster
di: Reinbigler, Marie, et al.
Pubblicazione: (2025)

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

Low-Cost Privacy-Preserving Decentralized Learning
di: Biswas, Sayan, et al.
Pubblicazione: (2024)

Fair Decentralized Learning
di: Biswas, Sayan, et al.
Pubblicazione: (2024)

Noiseless Privacy-Preserving Decentralized Learning
di: Biswas, Sayan, et al.
Pubblicazione: (2024)

Stabl: Blockchain Fault Tolerance
di: Gramoli, Vincent, et al.
Pubblicazione: (2024)

Approximate Byzantine Fault-Tolerance in Distributed Optimization
di: Liu, Shuo, et al.
Pubblicazione: (2021)

SWARM: Replicating Shared Disaggregated-Memory Data in No Time
di: Murat, Antoine, et al.
Pubblicazione: (2024)

uBFT: Microsecond-scale BFT using Disaggregated Memory [Extended Version]
di: Aguilera, Marcos K., et al.
Pubblicazione: (2022)

Efficient Signature-Free Validated Agreement
di: Civit, Pierre, et al.
Pubblicazione: (2024)

Partial Synchrony for Free? New Upper Bounds for Byzantine Agreement
di: Civit, Pierre, et al.
Pubblicazione: (2024)

Carbon: Scaling Trusted Payments with Untrusted Machines
di: Camaioni, Martina, et al.
Pubblicazione: (2022)

Accelerating MoE Model Inference with Expert Sharding
di: Balmau, Oana, et al.
Pubblicazione: (2025)

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

Catastrophic Forgetting Resilient One-Shot Incremental Federated Learning
di: Zaland, Obaidullah, et al.
Pubblicazione: (2026)

FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
di: Jhunjhunwala, Divyansh, et al.
Pubblicazione: (2024)

Chop Chop: Byzantine Atomic Broadcast to the Network Limit
di: Camaioni, Martina, et al.
Pubblicazione: (2023)

DSig: Breaking the Barrier of Signatures in Data Centers
di: Aguilera, Marcos K., et al.
Pubblicazione: (2024)

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

DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning
di: Luo, Kangyang, et al.
Pubblicazione: (2024)

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

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning
di: Lan, Muhang, et al.
Pubblicazione: (2025)

OFL-W3: A One-shot Federated Learning System on Web 3.0
di: Jiang, Linshan, et al.
Pubblicazione: (2024)

A House United Within Itself: SLO-Awareness for On-Premises Containerized ML Inference Clusters via Faro
di: Jeon, Beomyeol, et al.
Pubblicazione: (2024)

Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation
di: Zhang, Zikai, et al.
Pubblicazione: (2026)