raction of free-standing metadata describing learning objects is typified by an analytical model which primarily focuses on the encoding of discrete properties pertaining to the ...
In this paper we suggest that if semantics are to fullfil their potential in the learning domain then a paradigm shift in perspective is necessry from information based content de...
Feng Tao, David E. Millard, Arouna Woukeu, Hugh C....
In this theoretical contribution we provide mathematical proof that two of the most important classes of network learning - correlation-based differential Hebbian learning and rew...
Christoph Kolodziejski, Bernd Porr, Minija Tamosiu...
The objective of this work is to interpret inductive results obtained by the unsupervised learning method OSHAM. We briefly introduce the learning process of OSHAM, that extracts ...
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...