This paper proposes the use of uncertainty reduction in machine learning methods such as co-training and bilingual bootstrapping, which are referred to, in a general term, as ‘c...
We study statistical consistency of two recently proposed subspace identification algorithms for closed-loop systems. These algorithms een as implementations of an abstract state-...
Abstract. In artificial intelligence literature there is a rising interest in studying strategic interaction situations. In these situations a number of rational agents act strateg...
Abstract - In this paper, we present a rankrevealing two-sided orthogonal decomposition method for solving the STLS problem. An error analysis of the algorithm is given. Our numeri...
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...