Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
This paper presents a classification-driven biomedical image retrieval system to bride the semantic gap by transforming image features to their global categories at different gran...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
A novel three-stage method for the analysis of electroencephalographic (EEG) signals, concerning epileptic seizures, is proposed. First, segments of the EEG signals are analyzed u...
Alexandros T. Tzallas, Markos G. Tsipouras, Dimitr...