Nature Methods - A shortcut to high-dimensional data. Big data comes at a price, and it is a glutton for computer memory. Rather than using data compression to solve this problem, Cleary et al ...

Getting a high compression ratio is needed to address the increasing gap between the memory size and the storage system bandwidth and size in exascale systems. The EZ project is developing the SZ ...

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.

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.

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.