Abstract: The fusion of federated learning and differential privacy can provide more comprehensive and rigorous privacy protection, thus attracting extensive interests from both academia and industry.
Suppose a Jupyter Notebook client (for example, a tab in Google Chrome or Visual Studio Code) provides a JavaScript object whose methods you want to call from its corresponding Python kernel. For ...
Abstract: This paper focuses on a distributed nonsmooth composite optimization problem over a multiagent networked system, in which each agent is equipped with a local Lipschitz-differentiable ...
Developed to benchmark and explore the full capabilities of the Venice.ai API, the venice-ai Python package has evolved into a comprehensive client library for developers. This library provides ...
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