Companies trading stocks need to store information on stock prices over specific time intervals, which results in very large databases. Large quantities of numerical data (thousan...
Carmen Sanz Merino, Mike Sips, Daniel A. Keim, Chr...
Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, hu...
Data reduction plays an important role in machine learning and pattern recognition with a high-dimensional data. In real-world applications data usually exists with hybrid formats...
The management and the processing of Earth science data has been gaining importance over the last decade due to higher data volumes generated by a larger number of instruments and ...
Petr Votava, Rama Nemani, Keith Golden, Daniel E. ...
Accurate and precise estimation of the noise variance is often of key importance as an input parameter for posterior image processing tasks. In MR images, background data is well s...