Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...
Large repositories of source code create new challenges and opportunities for statistical machine learning. Here we first develop Sourcerer, an infrastructure for the automated c...
Erik Linstead, Paul Rigor, Sushil Krishna Bajracha...
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
To reduce the production cost of 3D-CG educational contents for e-Learning system and to improve the capability of self-learning system, we developed a new self-learning system ba...
Intelligent Tutoring Systems, while effective at producing student learning [2,7], are notoriously costly to construct [1,9], and require PhD level experience in cognitive science...
Neil T. Heffernan, Terrence E. Turner, Abraao L. N...