Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
Task partition is a critical problem of collaborative conceptual design. Aiming at the shortage that current task partition methods don't accord to innovative functional reas...
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
Protein structure comparison is important for elucidation of evolutionary relationships, function and functionally important amino acid residues. We propose Geometric Invariant bas...
The Semantic Web is facing the important challenge to maintain its promise of a real world-wide graph of interconnected resources. Unfortunately, while URIs almost guarantee a dir...