Refining with colors Mathematicians have developed various strategies to compare graphs. Since the 1970s, algorithms have been able to test graph isomorphism, but in exponential time.

Combined with algorithms that can handle such graphs it’s a great way to not only make the basic structure of a network clear, but also to model structures and systems.

Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

APL researchers have demonstrated that a quantum algorithm can be used to speed up an information analysis task that classical computers struggle to perform.

Another noteworthy development is a distributed algorithm for computing the weighted girth, which is the length of the minimum-weight cycle in a graph [2]. By adopting a randomised approach and ...

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

AI and graphs have a few things in common: they are multi-faceted, ubiquitous in their applications, and seeing rapid growth in the 2020s.

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 ...

“The new algorithm is a remarkable tour de force,” said Giuseppe Italiano, a computer scientist at Luiss University and a co-author of the 1996 paper describing what is now the second-fastest ...