We present an evolutionary clustering method which can be applied to multi-relational knowledge bases storing resource annotations expressed in the standard languages for the Sema...
We present a category learning vector quantization (cLVQ) approach for incremental and life-long learning of multiple visual categories where we focus on approaching the stability-...
Stephan Kirstein, Heiko Wersing, Horst-Michael Gro...
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...
It has been shown that self-organized maps, when adequately trained with the set of integers 1 to 32, lay out real numbers in a 2D map in an ordering that is superior to any of the...
The impact of learning algorithm optimization by means of parameter tuning is studied. To do this, two quality attributes, sensitivity and classification performance, are investig...