Spectral clustering is quite complex, but it can reveal patterns in data that aren't revealed by other clustering techniques. Data clustering is the process of grouping data items so that similar ...

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 ...

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 ...

Predicting functions of genes is an important issue in biology. Clustering gene expression profiles has been widely used for gene function prediction, but most clustering methods are unstable and ...

Virtualization and clustering can be two faces of the same coin. Computing virtualization is a very hot topic for data center managers. Whether the motivation is higher utilization, reduced management ...

Lossless or lossy: If you have big data, know what type of compression to use Your email has been sent Illustration: Lisa Hornung/iStockPhoto Must-read big data coverage What Powers Your Databases?

Part 2 benchmarks the compression algorithms. It will be published July 20. Analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) are generating a huge and rapidly growing flood ...

About every 10 minutes, it seems, a new article about a "revolutionary breakthrough" in AI hits my screen. A new approach, a new feature, billions of dollars this, AI agents that. It has been non-stop ...

In the ever-evolving landscape of data centers, Total Cost of Ownership (TCO) remains a critical metric. It encompasses all costs associated with data center infrastructure throughout its lifecycle, ...