Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
One of the most important tasks performed in the early stages of a data warehouse project is the analysis of the structure and content of the existing data sources and their inten...
Skeleton is a lower dimensional shape description of an object. The requirements of a skeleton differ with applications. For example, object recognition requires skeletons with pr...
Model-based development is becoming an increasingly common development methodology. In important domains like embedded systems already major parts of the code are generated from m...