Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
Interval data is attracting attention from the data analysis community due to its ability to describe complex concepts. Since clustering is an important data analysis tool, extendi...
This paper studies how to incorporate side information (such as users’ feedback) in measuring node proximity on large graphs. Our method (ProSIN) is motivated by the well-studie...
: For many years, physical asset indicators were the main evidence of an organization’s successful performance. However, the situation has changed following the revolution of inf...
In the half-century since the C-value paradox (the apparent lack of correlation between organismal genome size and morphological complexity) was described, there have been no expli...