Abstract. We present a null-space primal-dual interior-point algorithm for solving nonlinear optimization problems with general inequality and equality constraints. The algorithm a...
In this paper, we present an improved method for decomposing multivariate polynomials. This problem, also known as the Functional Decomposition Problem (FDP) [17, 9, 27], is class...
—A simple yet effective unsupervised classification rule to discriminate between normal and abnormal data is based on accepting test objects whose nearest neighbors’ distances ...
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
Random projection has been suggested as a means of dimensionality reduction, where the original data are projected onto a subspace using a random matrix. It represents a computati...
Tetsuya Takiguchi, Jeff Bilmes, Mariko Yoshii, Yas...