This paper connects two fundamental ideas from theoretical computer science: hard-core set construction, a type of hardness amplification from computational complexity, and boosti...
We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
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 model for human learning and decision making in environments of repeated Cliff-Edge (CE) interactions. In CE environments, which include common daily in...
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...