Asynchronous Federated Learning with non-convex client objective functions and heterogeneous dataset
Abstract: Federated Learning is a distributed machine learning paradigm that enables model training across decentralized devices holding local data, thereby preserving data privacy and reducing the ...
Your browser does not support the audio element. No frameworks, no funding, no team—just vanilla JavaScript and a real problem to solve. I got locked out of the GST ...
Async mapProfileToUser functions are accepted but silently drop all mapped fields. The core OAuth callback merges results without awaiting, causing the Promise object to be spread (no-op) instead of ...
Currently when passing #[automock] to a trait with async functions, it automatically generates Send for its return value to ensure thread safety. However, I am working on an async runtime that ...
In this tutorial, we demonstrate how to harness Crawl4AI, a modern, Python‑based web crawling toolkit, to extract structured data from web pages directly within Google Colab. Leveraging the power of ...
If you’re building a cloud-native application using a scalable cluster of microservices, you’re going to need a way for those services to communicate. Traditional API calls work well for tightly ...
Abstract: In the graph-based semi-supervised learning, the Green-function method is a classical method that works by computing the Green's function in the graph space. However, when applied to large ...
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