Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
The literature agrees that the major threat to IS security is constituted by careless employees who do not comply with organizations’ IS security policies and procedures. To add...
Investigations of software development practices, processes, and techniques frequently report separately on the costs and benefits of a phenomenon under study, but rarely adequate...
We propose a new semi-supervised model selection method that is derived by applying the structural risk minimization principle to a recent semi-supervised generalization error bou...