This paper describes a method for hierarchical reinforcement learning in which high-level policies automatically discover subgoals, and low-level policies learn to specialize for ...
In the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known...
In this paper, we propose a novel approach to automatic generation of summary templates from given collections of summary articles. This kind of summary templates can be useful in...
We propose a novel method for automatically discover-ing key motion patterns happening in a scene by observing the scene for an extended period. Our method does not rely on object ...
This paper explores correspondence and mixture topic modeling of documents tagged from two different perspectives. There has been ongoing work in topic modeling of documents with...