We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
Alternative splicing is a mechanism for generating different gene transcripts (called isoforms) from the same genomic sequence. Finding alternative splicing events experimentally ...
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Classification problems in critical applications such as health care or security often require very high reliability because of the high costs of errors. In order to achieve this r...