Search Results for author:
Found 2 papers, 1 papers with code
Randomized Quantization is All You Need for Differential Privacy in Federated Learning
To the best of our knowledge, this is the first study that solely relies on randomized quantization without incorporating explicit discrete noise to achieve Renyi DP guarantees in Federated Learning systems.
Online Kernel based Generative Adversarial Networks
We propose a novel approach that resolves many of these issues by relying on a kernel-based non-parametric discriminator that is highly amenable to online training---we call this the Online Kernel-based Generative Adversarial Networks (OKGAN).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
