Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
Background: With the advent of high-throughput proteomic experiments such as arrays of purified proteins comes the need to analyse sets of proteins as an ensemble, as opposed to t...
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
The problem of identifying deviating patterns in XML repositories has important applications in data cleaning, fraud detection, and stock market analysis. Current methods determine...
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...