Previous work on using external aggregate rating information showed that this information can be incorporated in several different types of recommender systems and improves their...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Content-based retrieval has emerged in the face of content explosion as a promising approach to information access. In this paper, we focus on the challenging issue of recognizing ...
Yi-Hsuan Yang, Yu-Ching Lin, Ya-Fan Su, Homer H. C...
Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...
Background: An important step in annotation of sequenced genomes is the identification of transcription factor binding sites. More than a hundred different computational methods h...
Geir Kjetil Sandve, Osman Abul, Vegard Walseng, Fi...