Stefan Werner

Privacy-Preserving Distributed Zeroth-Order Optimization

2020 · arXiv (Cornell University)

We develop a privacy-preserving distributed algorithm to minimize a regularized empirical risk function when the first-order information is not available and data is distributed over a multi-agent network. We employ a zeroth-order method to minimize …

Kernel Regression on Graphs in Random Fourier Features Space

2021

This work proposes an efficient batch-based implementation for kernel regression on graphs (KRG) using random Fourier features (RFF) and a low-complexity online implementation. Kernel regression has proven to be an efficient learning tool in the …

Networked Personalized Federated Learning Using Reinforcement Learning

2023

Personalized federated learning enables every edge device or group of edge devices within the distributed network to learn a device- or cluster-specific model tailored to their local needs. Data scarcity, however, makes it difficult to …