Documents in many corpora, such as digital libraries and webpages, contain both content and link information. In a traditional topic model which plays an important role in the uns...
For both single probability estimation trees (PETs) and ensembles of such trees, commonly employed class probability estimates correct the observed relative class frequencies in e...
The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generaliz...
In this paper, we propose to use hypergraphs as the model for images and pose image segmentation as a machine learning problem in which some pixels (called seeds) are labeled as t...
For the last ten years a lot of work has been devoted to propositionalization techniques in relational learning. These techniques change the representation of relational problems t...