Cover Image

Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Jianing, Chen, Evan, Han, Dong-Jun, Liu, Chaoyue, Brinton, Christopher G.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differentially-Private Multi-Tier Federated Learning
by: Chen, Evan, et al.
Published: (2024)

Adversarial Analysis of the Differentially-Private Federated Learning in Cyber-Physical Critical Infrastructures
by: Hossain, Md Tamjid, et al.
Published: (2022)

Efficient Language Model Architectures for Differentially Private Federated Learning
by: Ro, Jae Hun, et al.
Published: (2024)

Differentially Private Clustered Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)

Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning
by: Egger, Maximilian, et al.
Published: (2025)

Age Aware Scheduling for Differentially-Private Federated Learning
by: Lin, Kuan-Yu, et al.
Published: (2024)

Differentially Private Online Federated Learning with Correlated Noise
by: Zhang, Jiaojiao, et al.
Published: (2024)

ACCESS-FL: Agile Communication and Computation for Efficient Secure Aggregation in Stable Federated Learning Networks
by: Nazemi, Niousha, et al.
Published: (2024)

Gradient Correction in Federated Learning with Adaptive Optimization
by: Chen, Evan, et al.
Published: (2025)

Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)

Differentially Private Federated Learning With Time-Adaptive Privacy Spending
by: Kiani, Shahrzad, et al.
Published: (2025)

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

LiFeChain: Lightweight Blockchain for Secure and Efficient Federated Lifelong Learning in IoT
by: Chen, Handi, et al.
Published: (2025)

Efficient and Scalable Implementation of Differentially Private Deep Learning without Shortcuts
by: Beltran, Sebastian Rodriguez, et al.
Published: (2024)

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning
by: Zhao, Zhihui, et al.
Published: (2025)

DP$^2$-FedSAM: Enhancing Differentially Private Federated Learning Through Personalized Sharpness-Aware Minimization
by: Zhang, Zhenxiao, et al.
Published: (2024)

Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning
by: Shankar, Aditya, et al.
Published: (2024)

Comments on "Federated Learning with Differential Privacy: Algorithms and Performance Analysis"
by: Talaei, Mahtab, et al.
Published: (2024)

Secure and Privacy-Preserving Vertical Federated Learning
by: Jin, Shan, et al.
Published: (2026)

Lancelot: Towards Efficient and Privacy-Preserving Byzantine-Robust Federated Learning within Fully Homomorphic Encryption
by: Jiang, Siyang, et al.
Published: (2024)

Inclusive, Differentially Private Federated Learning for Clinical Data
by: Parampottupadam, Santhosh, et al.
Published: (2025)

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

TernaryVote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data
by: Jin, Richeng, et al.
Published: (2024)

The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective
by: Kang, Tianqu, et al.
Published: (2024)

LiteChain: A Lightweight Blockchain for Verifiable and Scalable Federated Learning in Massive Edge Networks
by: Chen, Handi, et al.
Published: (2025)

DP2Guard: A Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT
by: Han, Baofu, et al.
Published: (2025)

ADI: Adversarial Dominating Inputs in Vertical Federated Learning Systems
by: Pang, Qi, et al.
Published: (2022)

Privocracy: Online Democracy through Private Voting
by: Camponês, Pedro, et al.
Published: (2026)

Private Aggregation in Hierarchical Wireless Federated Learning with Partial and Full Collusion
by: Egger, Maximilian, et al.
Published: (2023)

PCDM: A Diffusion-Based Data Poisoning Attack Against Federated Learning Systems
by: Sun, Wei, et al.
Published: (2026)

T-Watch: Towards Timed Execution of Private Transaction in Blockchains
by: Li, Chao, et al.
Published: (2024)

HERL: Tiered Federated Learning with Adaptive Homomorphic Encryption using Reinforcement Learning
by: Tang, Jiaxang, et al.
Published: (2024)

Fantastyc: Blockchain-based Federated Learning Made Secure and Practical
by: Boitier, William, et al.
Published: (2024)

Differential Privacy for Secure Machine Learning in Healthcare IoT-Cloud Systems
by: Mangala, N, et al.
Published: (2025)

Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System
by: Madduri, Ravi, et al.
Published: (2024)

Federated Analytics-Empowered Frequent Pattern Mining for Decentralized Web 3.0 Applications
by: Wang, Zibo, et al.
Published: (2024)

When Quantum Federated Learning Meets Blockchain in 6G Networks
by: Nguyen, Dinh C., et al.
Published: (2025)

DarkFed: A Data-Free Backdoor Attack in Federated Learning
by: Li, Minghui, et al.
Published: (2024)

Zero-Knowledge Proof-Based Consensus for Blockchain-Secured Federated Learning
by: Fu, Tianxing, et al.
Published: (2025)

DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation
by: Xu, Jie, et al.
Published: (2024)