1. A method for training a transductive support vector machine based on an objective function, the objective function based on a set of labeled training data classified into first and second classes and a set of unlabeled test data, comprising: decomposing the objective function into a sum of a concave function and a convex function; and determining a hyperplane classifier classifying the unlabeled data into the first and second classes by iteratively approximating the concave and convex functions.