In this paper, we propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our...
This paper presents a novel method for DNA microarray gridding based on Support Vector Machine (SVM) classifiers. It employs a set of soft-margin SVMs to estimate the lines of the ...
Dimitris G. Bariamis, Dimitris Maroulis, Dimitrios...
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....
Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structu...