This paper presents a semantic-aware classification algorithm that can leverage the interoperability among semantically heterogeneous learning object repositories using different ...
Ming-Che Lee, Kun Hua Tsai, Tung Cheng Hsieh, Ti K...
Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning...
Background: Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic d...
This paper presents Lecomps5, a web-based system for automated course personalization in distance learning environments. This system is an upgraded version of the Lecomps4 system,...
Carla Limongelli, Filippo Sciarrone, Marco Temperi...
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...