Graph algorithms and network analysis form the backbone of modern computational techniques used to decode the complex structures and dynamic behaviours exhibited by diverse real-world networks. From ...

Network design problems constitute a critical area in operations research and engineering, where the objective is to construct or upgrade network infrastructures optimally under a range of constraints ...

Editor’s note, February 2nd 2024: This article was updated after Meta announced earnings results for 2023. Facebook may be turning 20 on February 4th, but it is just as much of a magnet for ...

We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine data processing and problem-solving.

When Edsger W. Dijkstra published his algorithm in 1959, computer networks were barely a thing. The algorithm in question found the shortest path between any two nodes on a graph, with a variant ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of ...

From powering search engines to securing data and optimizing networks, algorithms underpin nearly every aspect of modern technology. Understanding how efficiently they can solve problems — and where ...

Physicists have devised an algorithm that provides a mathematical framework for how learning works in lattices called mechanical neural networks. It's easy to think that machine learning is a ...