This empirical study demonstrates that students’ learning of computer science takes place in qualitatively different ways. The results consist of categories, where each category...
Maintaining high annotation consistency in large corpora is crucial for statistical learning; however, such work is hard, especially for tasks containing semantic elements. This p...
Meta-learning is an efficient approach in the field of machine learning, which involves multiple classifiers. In this paper, a meta-learning framework consisting of stacking meta-...
A machine learning method is introduced here to improve the accuracy of brain registration. Generally, different brain regions might need different types or sets of features for r...
Concept learning in content-based image retrieval (CBIR) systems is a challenging task. This paper presents an active concept learning approach based on mixture model to deal with...