1. A computer implemented method for reducing computation time of an information processing system when selecting features from a feature space to train one or more algorithms, the computer implemented method comprising: receiving, by a feature selection circuit, a set of training samples and a set of test samples, wherein each of the set of training samples comprises a set of features and a target value, and wherein the set of test samples comprises the set of features absent the target value; training, by the feature selection circuit, one or more learning algorithms based on subset of the set of features; and reducing, by the feature selection circuit, computation time of the information processing system during the training of the one or more learning algorithms, wherein reducing the computation time comprises: determining a first centered Gram matrix of a given dimension for each of a set of feature vectors comprising at least one of the set of training samples and at least one of the set of test samples; determining a second centered Gram matrix of the given dimension for a target value vector comprising the target values from the set of training samples; and selecting a subset of features from the set of features based on the first and second centered Gram matrices.