This paper presents a control structure for general purpose image understanding that addresses both the high level of uncertainty in local hypotheses and the computational complex...
Estimation of distribution algorithms replace the typical crossover and mutation operators by constructing a probabilistic model and generating offspring according to this model....
We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial matrix to polynomial matrix multiplication. For an input n×n matrix of degree d over ...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...