Biclustering refers to simultaneous clustering of objects and their features. Use of biclustering is gaining momentum in areas such as text mining, gene expression analysis and co...
Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-...
Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structu...
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...