Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

Abstract: Influence maximization is one of the important problems in network science, data mining, and social media analysis. It focuses on identifying the most influential individuals (or nodes) in a ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

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 ...

Abstract: In social network analysis, the opinion maximization (OM) problem aims to locate several nodes as a seed set, which starts the information propagation and achieves the most positive opinion ...

A new gene editor takes advantage of CRISPR-associated proteins to insert whole genes into the genome, scientists report. When you purchase through links on our site, we may earn an affiliate ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

The rules of the LinkedIn game change all the time and you have to keep up if you want to win. Don't get caught out doing what worked in 2020. It doesn't work now. Your ideal customers are right there ...

The library sorting problem is used across computer science for organizing far more than just books. A new solution is less than a page-width away from the theoretical ideal. Computer scientists often ...