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 ...
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 ...
In a bid to more aggressively compete with rival AI companies like Google, OpenAI is launching Flex processing, an API option that provides lower AI model usage prices in exchange for slower response ...
LLMs enable interactions with external tools and data sources, such as weather APIs or calculators, through function calls, unlocking diverse applications like autonomous AI agents and neurosymbolic ...
Abstract: This article addresses the problem of finite-time asynchronous switching control for fuzzy Markov jump systems (FMJSs) using polynomial membership functions. Firstly, a Lyapunov-Krasovskii ...
Introduction: Leadless pacemakers (LPs) provide effective ventricular pacing without the risk associated with leads and pulse generators required for transvenous pacemakers. LPs are appealing for ...
var a, async = function(f) { setTimeout(function() { var r = 'step 2'; f(r); }, 1); }, myFunc = function() { a = 'step 1'; async(function(r) { a = r; // should reset ...
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