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. ...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Abstract. In this paper we consider the question of whether it is possible to classify n-back EEG data into different memory loads across subjects. To capture relevant information ...
Classifier subset selection (CSS) from a large ensemble is an effective way to design multiple classifier systems (MCSs). Given a validation dataset and a selection criterion, the...
We consider the problem of collective decision-making from an arbitrary set of classifiers under Sugeno fuzzy integral (S-FI). We assume that classifiers are given, i.e., they can...
Pilar Bulacio, Serge Guillaume, Elizabeth Tapia, L...