Facility location and clustering algorithms constitute a critical area of research that bridges optimisation theory and data analysis. Facility location techniques focus on the strategic placement of ...

As distribution companies absorb electric vehicle (EV) load growth, aging assets, extreme weather and a decarbonizing grid, ...

Co-clustering algorithms and models represent a robust framework for the simultaneous partitioning of the rows and columns in a data matrix. This dual clustering approach, often termed block ...

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 ...

Clustering algorithms are used to generate clusters of elements having similar characteristics. Among the different groups of clustering algorithms, agglomerative algorithm is widely used in the ...

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...

Clustering non-numeric -- or categorial -- data is surprisingly difficult, but it's explained here by resident data scientist Dr. James McCaffrey of Microsoft Research, who provides all the code you ...

PSMA-based PET imaging in newly diagnosed, high-risk localized prostate cancer, a National Cancer Institute (NCI) Cancer Moonshot trial. This is an ASCO Meeting Abstract from the 2025 ASCO ...

Artificial intelligence comes from machines - and precisely for that reason, it isn't automatically fair. Doctoral researcher Lena Krieger works at ...