In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive ...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
We explore algorithms for learning classification procedures that attempt to minimize the cost of misclassifying examples. First, we consider inductive learning of classification ...
Michael J. Pazzani, Christopher J. Merz, Patrick M...
In this paper, a novel diagnosis method is proposed. The proposed technique uses machine learning techniques instead of traditional cause-effect and/or effect-cause analysis. The ...
New Technologies have been incorporated to schools as learning tools some time ago. In this paper we remark some advantages of video games as educational systems and how we can us...