Machine Learning (ML) is increasingly used to implement advanced applications with non-deterministic behavior, which operate on the cloud-edge continuum. The pervasive adoption of ML is urgently calling for assurance solutions assessing applications non-f…

Livestream powered by baiosphere – the bavarian ai networkHow could machines learn as efficiently as humans and animals? How could machines learn to reason a…

Geometric Deep Learning Models for Vehicle Routing Problem – GitHub – isotlaboratory/ml4vrp: Geometric Deep Learning Models for Vehicle Routing Problem…

Machine Learning Engineering Guides and Tools. Contribute to stas00/ml-engineering development by creating an account on GitHub.

Discover A Hands-On Introduction to Machine Learning, 1st Edition, Chirag Shah, HB ISBN: 9781009123303 on Higher Education from Cambridge…

Compute, data, and algorithmic advances are the three fundamental factors that guide the progress of modern Machine Learning (ML). In this paper we study trends in the most readily quantified factor – compute. We show that before 2010 training compute gre…

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offe…

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offe…

This paper reviews the recent literature on solving the Boolean satisfiability problem (SAT), an archetypal NP-complete problem, with the help of machine learning techniques. Despite the great success of modern SAT solvers to solve large industrial instan…