We consider ranking and clustering problems related to the aggregation of inconsistent information, in particular, rank aggregation, (weighted) feedback arc set in tournaments, consensus and ...

Algorithms define the rules, conditions, and methodology that an AI will use when processing and analyzing data. Written by eWEEK content and product recommendations are editorially independent. We ...

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets. Data clustering is the process of placing data items ...

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 ...

AbstractDeep optical images are often crowded with overlapping objects. This is especially true in the cores of galaxy clusters, where images of dozens of galaxies may lie atop one another. Accurate ...

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...