In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
A pervasive problem in large relational databases is identity uncertainty which occurs when multiple entries in a database refer to the same underlying entity in the world. Relati...
IMS Learning Design (LD) is a specification that aims at computationally representing any learning process. However, the possibilities of LD to represent collaborative learning sce...
: This paper is concerned with relational Support Vector Machines, at the intersection of Support Vector Machines (SVM) and relational learning or Inductive Logic Programming (ILP)...
This paper presents a dissertation project on business-integrated, service-oriented learning architectures. The isolation of corporate learning management from core business functi...