Cover Image

ADP-VRSGP: Decentralized Learning with Adaptive Differential Privacy via Variance-Reduced Stochastic Gradient Push

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Xiaoming, Liu, Teng, Wang, Xin, Yang, Ming, Yu, Jiguo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DFPL: Decentralized Federated Prototype Learning Across Heterogeneous Data Distributions
by: Zhang, Hongliang, et al.
Published: (2025)

Adaptive Weighting Push-SUM for Decentralized Optimization with Statistical Diversity
by: Zhou, Yiming, et al.
Published: (2024)

Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient
by: Deng, Xiaoge, et al.
Published: (2021)

PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
by: Zhang, Hongliang, et al.
Published: (2025)

Decentralized Federated Averaging via Random Walk
by: Wang, Changheng, et al.
Published: (2025)

Distributed Stochastic Gradient Descent with Staleness: A Stochastic Delay Differential Equation Based Framework
by: Yu, Siyuan, et al.
Published: (2024)

Differentially Private Perturbed Push-Sum Protocol and Its Application in Non-Convex Optimization
by: Zhou, Yiming, et al.
Published: (2026)

Optimizing Stochastic Gradient Push under Broadcast Communications
by: Nguyen, Tuan, et al.
Published: (2026)

Fault-Tolerant Decentralized Distributed Asynchronous Federated Learning with Adaptive Termination Detection
by: Akkinepally, Phani Sahasra, et al.
Published: (2025)

Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
by: Han, Xuefeng, et al.
Published: (2024)

Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex Optimization
by: Lin, Zhenwei, et al.
Published: (2023)

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

Biased Compression in Gradient Coding for Distributed Learning
by: Li, Chengxi, et al.
Published: (2026)

DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations
by: Yang, Minghao, et al.
Published: (2024)

Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates
by: Xiong, Guojun, et al.
Published: (2023)

An Adaptive Differential Privacy Method Based on Federated Learning
by: Wang, Zhiqiang, et al.
Published: (2024)

Vanishing Variance Problem in Fully Decentralized Neural-Network Systems
by: Tian, Yongding, et al.
Published: (2024)

Robust Decentralized Learning with Local Updates and Gradient Tracking
by: Ghiasvand, Sajjad, et al.
Published: (2024)

Decentralized Personalization for Federated Medical Image Segmentation via Gossip Contrastive Mutual Learning
by: Chen, Jingyun, et al.
Published: (2025)

A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration
by: Hu, Yuchen, et al.
Published: (2025)

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

Cooperative Gradient Coding
by: Weng, Shudi, et al.
Published: (2025)

An Accurate Beam-Tracking Algorithm with Adaptive Beam Reconstruction via UAV-BSs for Mobile Users
by: Zhang, Jing, et al.
Published: (2024)

Bandwidth-Aware Network Topology Optimization for Decentralized Learning
by: Shen, Yipeng, et al.
Published: (2025)

Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning
by: Yang, Hansi, et al.
Published: (2024)

Enhancing Privacy in Decentralized Min-Max Optimization: A Differentially Private Approach
by: Quan, Yueyang, et al.
Published: (2025)

Towards Communication-Efficient Decentralized Federated Graph Learning over Non-IID Data
by: Wang, Shilong, et al.
Published: (2025)

Accelerating OpenPangu Inference on NPU via Speculative Decoding
by: Dai, Yuntao, et al.
Published: (2026)

Arrow: Adaptive Scheduling Mechanisms for Disaggregated LLM Inference Architecture
by: Wu, Yu, et al.
Published: (2025)

Lattica: A Decentralized Cross-NAT Communication Framework for Scalable AI Inference and Training
by: Yang, Ween, et al.
Published: (2025)

Graph-based Gossiping for Communication Efficiency in Decentralized Federated Learning
by: Nguyen, Huong, et al.
Published: (2025)

DynaShard: Secure and Adaptive Blockchain Sharding Protocol with Hybrid Consensus and Dynamic Shard Management
by: Liu, Ao, et al.
Published: (2024)

FedAdaVR: Adaptive Variance Reduction for Robust Federated Learning under Limited Client Participation
by: Howlader, S M Ruhul Kabir, et al.
Published: (2026)

Key-Embedded Privacy for Decentralized AI in Biomedical Omics
by: Zhang, Rongyu, et al.
Published: (2026)

PRISM: Dynamic Primitive-Based Forecasting for Large-Scale GPU Cluster Workloads
by: Wu, Xin, et al.
Published: (2026)

Distributed Deep Learning using Stochastic Gradient Staleness
by: Pham, Viet Hoang, et al.
Published: (2025)

Divergence-Based Adaptive Aggregation for Byzantine Robust Federated Learning
by: Xiao, Bingnan, et al.
Published: (2026)

Tackling Privacy Heterogeneity in Differentially Private Federated Learning
by: Xu, Ruichen, et al.
Published: (2026)

Lightweight Federated Learning with Differential Privacy and Straggler Resilience
by: Hong, Shu, et al.
Published: (2024)

SDFLMQ: A Semi-Decentralized Federated Learning Framework over MQTT
by: Ali-Pour, Amir, et al.
Published: (2025)