Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learnin...
Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S...
In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. Duri...
We look at distributed representation of structure with variable binding, that is natural for neural nets and allows traditional symbolic representation and processing. The repres...
Abstract. An efficient low-level word image representation plays a crucial role in general cursive word recognition. This paper proposes a novel representation scheme, where a word...
Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Domi...
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...