Data clustering remains an essential component of unsupervised learning, enabling the exploration and interpretation of complex datasets. The field has witnessed considerable advancements that address ...

Did you know that the tools used for analyzing relationships between social network users or ranking web pages can also be extremely valuable for making sense of big science data? On a social network ...

Back in the hazy olden days of the pre-2000s, navigating between two locations generally required someone to whip out a paper map and painstakingly figure out the most optimal route between those ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...

Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a ...

Recently, Applied Mathematics graduate student Alec Dunton and his team won the Graph Challenge as a part of his summer internship at Lawrence Livermore National Laboratory. The GraphChallenge, as ...

A puzzle that has long flummoxed computers and the scientists who program them has suddenly become far more manageable. A new algorithm efficiently solves the graph isomorphism problem, computer ...

Researchers took one of the most popular clustering approaches in modern biology -- Markov Clustering algorithm -- and modified it to run efficiently and at scale on supercomputers. Their algorithm ...