Distributed algorithms for graph problems represent a vibrant area of study that addresses the challenges of decentralised computation across interconnected networks. By partitioning complex graph ...

Graph cover problems form a critical area within discrete optimisation and theoretical computer science, addressing the challenge of selecting subsets of vertices (or edges) that satisfy predetermined ...

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 ...

Motif-based graph local clustering is a popular method for graph mining tasks due to its various applications, such as community detection, network optimization and graph learning. However, the ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now DeepMind wants to enable neural networks to ...

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory. This past October, as Jacob Holm and Eva Rotenberg were thumbing through a ...

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 ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

Like the core algorithm, Google’s Knowledge Graph periodically updates. But little has been known about how, when, and what it means — until now. I believe these updates consist of three things: ...

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