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cs.CR2026
Improving Parameter-Efficient Federated Learning with Differentially Private Refactorization
Linh Tran, Ana Milanova, Stacy Patterson
Federated Learning (FL) with parameter-efficient fine-tuning, such as Low-Rank Adaptation (LoRA), enables scalable model training on distributed data. However, when combined with D…
cs.CR2024
A Differentially Private Blockchain-Based Approach for Vertical Federated Learning
Linh Tran, Sanjay Chari, Md. Saikat Islam Khan +3
We present the Differentially Private Blockchain-Based Vertical Federal Learning (DP-BBVFL) algorithm that provides verifiability and privacy guarantees for decentralized applicati…
cs.CR2024★ 5 cited
A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective
Lei Yu, Meng Han, Yiming Li +8
Vertical Federated Learning (VFL) is a federated learning paradigm where multiple participants, who share the same set of samples but hold different features, jointly train machine…