Abstract. In this paper we introduce a new technique for approximation schemes for geometrical optimization problems. As an example problem, we consider the following variant of th...
We show that it is not possible to approximate the minimum Steiner tree problem within 1 + 1 162 unless RP = NP. The currently best known lower bound is 1 + 1 400. The reduction i...
In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay's evidence approximation. The model is re-p...
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show (1) how to appro...
In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...