Put simply, smoothed analysis introduces small random perturbations to the connections in a graph rather than focusing purely ...

Graph analysis has long been used modeling customer ... as well as on machine learning algorithms, that can find dynamic influence patterns within complex sensor-data sets. For example, how ...

Development of more sophisticated ideas in data type and structure, with an introduction to the connection between data structures and the algorithms they support. Data abstraction. Controlled access ...

Graphs are collections of nodes connected by edges ... “We very quickly realized that with this new analysis, a conceptually very, very simple algorithm will solve the problem,” said Holm. The new ...

The next level up in sophistication is the graph algorithm. In this case, the query is perhaps using a function of some sort that runs an algorithm over not just simply selecting and grouping ...

Graph mining algorithms typically focus on finding dense connections between individual pairs of points, such as two people who frequently communicate on social media. However, the researchers ...

There are many graph algorithms around, and each algorithm can provide insights for different data analysis scenarios. When cuGraph's first official release, 0.6, came out in late March ...

Sure, there are graph databases like Neo4j, but graph analysis or graph search may be more useful, depending on the sorts of data relationships you need to explore Graph processing is hot right ...