Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
The goal of performance analysis of business processes is to gain insights into operational processes, for the purpose of optimizing them. To intuitively show which parts of the pr...
Background: At intermediate stages of genome assembly projects, when a number of contigs have been generated and their validity needs to be verified, it is desirable to align thes...