We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Mitchell et al. (2008) demonstrated that corpus-extracted models of semantic knowledge can predict neural activation patterns recorded using fMRI. This could be a very powerful te...
We present the first unsupervised approach to the problem of learning a semantic parser, using Markov logic. Our USP system transforms dependency trees into quasi-logical forms, r...
In this paper, we are interested in the qualitative knowledge that underlies some given probabilistic information. To represent such qualitative structures, we use ordinal conditi...
Gabriele Kern-Isberner, Matthias Thimm, Marc Finth...
This paper introduces a Self-Similarity Matrix (SSM) based video copy detection scheme and a Visual Character-String (VCS) descriptor for SSM matching. SSM, which exploits the spa...