Simplex optimization is one of the simplest algorithms available to train a neural network. Understanding how simplex optimization works, and how it compares to the more commonly used back-propagation ...

A team of computer scientists has come up with a dramatically faster algorithm for one of the oldest problems in computer science: maximum flow. The problem asks how much material can flow through a ...

The original version of this story appeared in Quanta Magazine. If you’ve been making the same commute for a long time, you’ve probably settled on what seems like the best route. But “best” is a ...

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 ...

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 ...

We consider discounted Markov decision processes (MDPs) with countably-infinite state spaces, finite action spaces, and unbounded rewards. Typical examples of such MDPs are inventory management and ...