Publications (50)
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…
Compressed Learning for Tactile Object Classification
Brayden Hollis, Stacy Patterson, Jeff Trinkle
The potential of large tactile arrays to improve robot perception for safe operation in human-dominated environments and of high-resolution tactile arrays to enable human-level dex…
Optimizing the Coherence of Composite Networks
Erika Mackin, Stacy Patterson
We consider how to connect a set of disjoint networks to optimize the performance of the resulting composite network. We quantify this performance by the coherence of the composite…
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…
Flexible Vertical Federated Learning with Heterogeneous Parties
Timothy Castiglia, Shiqiang Wang, Stacy Patterson
We propose Flexible Vertical Federated Learning (Flex-VFL), a distributed machine algorithm that trains a smooth, non-convex function in a distributed system with vertically partit…
Distributed Sparse Signal Recovery For Sensor Networks
Stacy Patterson, Yonina C. Eldar, Idit Keidar
We propose a distributed algorithm for sparse signal recovery in sensor networks based on Iterative Hard Thresholding (IHT). Every agent has a set of measurements of a signal x, an…