Correlation clustering is a framework for partitioning the nodes of a graph according to pairwise similarity and dissimilarity labels on edges. Rather than fixing the number of clusters in advance, ...

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

Property testing in graph theory concerns the design of sublinear‐time algorithms that, given query access to a large graph, swiftly distinguish between the case where the graph satisfies a global ...

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

Graph database vendor Neo4j Inc. is teaming up with Snowflake Inc. to make a library of Neo4j’s graph analytics functions available in the Snowflake cloud. The deal announced today allows users to ...

This is a graduate-level course on theoretical aspects of Big Data. We will examine algorithms and data structures for dealing with massive data sets. We will discuss such topics as streaming ...

Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

How to recognize and use array and list data structures in your Java programs. Which algorithms work best with different types of array and list data structures. Why some algorithms will work better ...