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...
Support Vector Machine (SVM) has been spotlighted in the machine learning community thanks to its theoretical soundness and practical performance. When applied to a large data set...
In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
We describe an algorithm for support vector machines (SVM) that can be parallelized efficiently and scales to very large problems with hundreds of thousands of training vectors. I...
In this paper, a novel method of relevance feedback is presented based on Support Vector Machine learning in the content-based image retrieval system. A SVM classifier can be lear...