Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...

Graph algorithms constitute a pivotal component of modern computational science, underpinning diverse applications ranging from transportation optimisation and telecommunications to social network ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...

This is a graduate-level course on theoretical aspects of Big Data. We will examine algorithms and data structures for dealing with massive data sets. We will discuss such topics as streaming ...

A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs. Nvidia has long ago stopped ...

The massive datasets that power machine learning algorithms and systems are complex, noisy, and vulnerable to various kinds of errors, contamination, and adversarial corruptions. As data science and ...

There is a new sorting algorithm a deterministic O(m log2/3 n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that compute shortest paths through vast networks. Now imagine scaling that task ...