Image de couverture de livre

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Liu, Bing, Zhao, Chengcheng, Chai, Li, Cheng, Peng, Wang, Yaonan
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Byzantine-Resilient Federated Learning via Distributed Optimization
par: Xia, Yufei, et autres
Publié: (2025)

Private Aggregation for Byzantine-Resilient Heterogeneous Federated Learning
par: Egger, Maximilian, et autres
Publié: (2025)

Trade-off in Estimating the Number of Byzantine Clients in Federated Learning
par: Chen, Ziyi, et autres
Publié: (2025)

H+: An Efficient Similarity-Aware Aggregation for Byzantine Resilient Federated Learning
par: Zuo, Shiyuan, et autres
Publié: (2025)

Robust Decentralized Multi-armed Bandits: From Corruption-Resilience to Byzantine-Resilience
par: Hu, Zicheng, et autres
Publié: (2025)

Tight Regret Bounds for Bilateral Trade under Semi Feedback
par: Jin, Yaonan
Publié: (2026)

Byzantine Resilient Federated Multi-Task Representation Learning
par: Le, Tuan, et autres
Publié: (2025)

Byzantine-Robust Distributed Sparse Learning Revisited
par: Wang, Yuxuan, et autres
Publié: (2026)

TernaryVote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data
par: Jin, Richeng, et autres
Publié: (2024)

Distribution-Centric Policy Optimization Dominates Exploration-Exploitation Trade-off
par: Li, Zhaochun, et autres
Publié: (2026)

Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
par: Zuo, Shiyuan, et autres
Publié: (2024)

On the Trade-off between Flatness and Optimization in Distributed Learning
par: Cao, Ying, et autres
Publié: (2024)

Improving $(α, f)$-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distance
par: García-Márquez, Mario, et autres
Publié: (2025)

Byzantine-Resilient Decentralized Multi-Armed Bandits
par: Zhu, Jingxuan, et autres
Publié: (2023)

Rethinking Bregman Divergences in Kronecker-Factored Optimizers
par: Liu, Bing, et autres
Publié: (2026)

Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing
par: Fang, Minghong, et autres
Publié: (2025)

Partial Model Sharing Improves Byzantine Resilience in Federated Conformal Prediction
par: Lari, Ehsan, et autres
Publié: (2026)

Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
par: Li, Bo, et autres
Publié: (2024)

On the Byzantine-Resilience of Distillation-Based Federated Learning
par: Roux, Christophe, et autres
Publié: (2024)

The Rate-Distortion-Perception Trade-off: The Role of Private Randomness
par: Hamdi, Yassine, et autres
Publié: (2024)

Accelerating Byzantine-Robust Distributed Learning with Compressed Communication via Double Momentum and Variance Reduction
par: Li, Yanghao, et autres
Publié: (2026)

A Weighted Gradient Tracking Privacy-Preserving Method for Distributed Optimization
par: Xie, Furan, et autres
Publié: (2025)

Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning
par: Liu, Bing, et autres
Publié: (2025)

Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
par: Li, Yuecheng, et autres
Publié: (2024)

Byzantine-Resilient Over-the-Air Federated Learning under Zero-Trust Architecture
par: Yao, Jiacheng, et autres
Publié: (2025)

Privacy-Preserving Resilient Vector Consensus
par: Liu, Bing, et autres
Publié: (2024)

Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity
par: Shi, Qiankun, et autres
Publié: (2025)

Tacit Learning with Adaptive Information Selection for Cooperative Multi-Agent Reinforcement Learning
par: Liu, Lunjun, et autres
Publié: (2024)

MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization
par: Zhao, Yang, et autres
Publié: (2026)

Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity
par: Wang, Shixiong, et autres
Publié: (2023)

Perfect Privacy for Discriminator-Based Byzantine-Resilient Federated Learning
par: Xia, Yue, et autres
Publié: (2025)

GRANITE : a Byzantine-Resilient Dynamic Gossip Learning Framework
par: Belal, Yacine, et autres
Publié: (2025)

Coded Robust Aggregation for Distributed Learning under Byzantine Attacks
par: Li, Chengxi, et autres
Publié: (2025)

Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering
par: Liu, Changxin, et autres
Publié: (2024)

Communication-Efficient Byzantine-Resilient Federated Zero-Order Optimization
par: Neto, Afonso de Sá Delgado, et autres
Publié: (2024)

Distributed Online Private Learning of Convex Nondecomposable Objectives
par: Cheng, Huqiang, et autres
Publié: (2022)

Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization
par: Salgia, Sudeep, et autres
Publié: (2025)

When to Forget? Complexity Trade-offs in Machine Unlearning
par: Van Waerebeke, Martin, et autres
Publié: (2025)

Deep Learning for Resilient Adversarial Decision Fusion in Byzantine Networks
par: Kallas, Kassem
Publié: (2024)

BRFL: A Blockchain-based Byzantine-Robust Federated Learning Model
par: Li, Yang, et autres
Publié: (2023)