Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
Abstract. Parthood is a relation of fundamental importance in a number of disciplines including cognitive science, linguistics and conceptual modeling. However, one classical probl...
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
We present a new generative model for relational data in which relations between objects can have either a binding or a separating effect. For example, in a group of students sep...