This paper presents an extensive evaluation, on artificial datasets, of EDY, an unsupervised algorithm for automatically synthesizing a Structured Hidden Markov Model (S-HMM) from ...
Many real-world problems are inherently hierarchically structured. The use of this structure in an agent’s policy may well be the key to improved scalability and higher performa...
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Craig Saunders, John Shawe-Taylor, Juho Rousu, S&a...
We present a novel approach to natural language generation (NLG) that applies hierarchical reinforcement learning to text generation in the wayfinding domain. Our approach aims to...
A variety of flexible models have been proposed to detect
objects in challenging real world scenes. Motivated
by some of the most successful techniques, we propose a
hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...