Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
The present paper reports on an end-to-end application using a deep processing grammar to extract spatial and temporal information of prepositional and adverbial expressions from ...
Lars Hellan, Dorothee Beermann, Jon Atle Gulla, At...
In multimodal function optimization, niching techniques create diversification within the population, thus encouraging heterogeneous convergence. The key to the effective diversif...
Semantic taxonomies such as WordNet provide a rich source of knowledge for natural language processing applications, but are expensive to build, maintain, and extend. Motivated by...
Topology control protocols attempt to reduce the energy consumption of nodes in an ad-hoc wireless network while maintaining sufficient network connectivity. Topology control proto...
Sukumar Ghosh, Kevin M. Lillis, Saurav Pandit, Sri...