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

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 ...

Graph analytics improves AI decision-making by uncovering hidden patterns and relationships in complex data, delivering more accurate insights with richer context than traditional analytics. Yet ...

Graph algorithms constitute a fundamental area of computational research that focuses on the analysis and manipulation of graph structures, which represent systems of interconnected entities. In ...

CATALOG DESCRIPTION: Design and analysis of advanced algorithms: graph algorithms; maximal network flows; min-cost flow algorithms; convex cost flows. REQUIRED TEXT ...

This idea holds significant weight when discussing the production of specific results with generative AI, and harvesting the latest trends. Given that many AI systems are general-purpose, it prompts ...

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

Advanced graph algorithms and embeddings, such as centrality, pathfinding, community detection, link prediction, and similarity, dramatically improve outcomes across hundreds of use cases such as ...