Abstract. We consider an approach to service selection wherein service consumers choose services with desired nonfunctional properties to maximize their utility. A consumer’s uti...
Bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retr...
In this paper, a novel multiresolution algorithm for registering multimodal images, using an adaptive Monte Carlo scheme is presented. At each iteration, random solution candidates...
— A new decoding algorithm, referred to as Min-Sum with Adaptive Message Control (AMC-MS), is proposed to reduce the decoding complexity of nonbinary LDPC codes. The proposed alg...
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...