However, the expansion into high-dimensional data science, supported by large-scale datasets and ML techniques, is enhancing the ability to decipher more complex structure-property relationships.

Statisticians from the National University of Singapore (NUS) have introduced a new technique that accurately describes high-dimensional data using lower-dimensional smooth structures. This ...

Alireza Doostan is leading a major effort for real-time data compression for supercomputer research.. A professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences at the ...

This model could be considered a four-dimensional model. You could choose to visualize this data in a table, or you could try to represent it as a picture. To get there, you would have to use vectors.

New data compression method reduces big-data bottleneck; outperforms, enhances JPEG. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2013 / 12 / 131219131237.htm ...

Hotspots—areas of unusually high activity, such as a sudden surge in transactions from a specific region or device—often signal potential fraud, making their real-time identification critical.

In high dimensional data, clusters of objects often exist in subspaces rather than in the entire space. This is the data sparsity problem faced in clustering high-dimensional data.

Jan 29, 2024: A manifold fitting approach for high-dimensional data reduction beyond Euclidean space (Nanowerk News) National University of Singapore (NUS) statisticians have introduced a new ...