We describe an algorithm for support vector machines (SVM) that can be parallelized efficiently and scales to very large problems with hundreds of thousands of training vectors. I...
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...
: This paper presents an overview over parallel architectures for the efficient realisation of digital libraries by considering image databases as an example. The state of the art ...
Dynamic Datastructure Excavation (DDE) is a new approach to extract datastructures from C binaries without any need for debugging symbols. Unlike most existing tools, DDE uses dyn...