In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
Recent advances of robotic/mechanical devices enable us to measure a subject's performance in an objective and precise manner. The main issue of using such devices is how to r...
Jae-Yoon Jung, Janice I. Glasgow, Stephen H. Scott
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
Presently, inductive learning is still performed in a frustrating batch process. The user has little interaction with the system and no control over the final accuracy and traini...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo, S...
In this paper we present extended definitions of k-anonymity and use them to prove that a given data mining model does not violate the k-anonymity of the individuals represented in...