In this paper we examine the problem of estimating the parameters of a multinomial distribution over a large number of discreteoutcomes,most of which do not appearin the training ...
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Background: Haplotypes extracted from human DNA can be used for gene mapping and other analysis of genetic patterns within and across populations. A fundamental problem is, howeve...
We study minimum-cost sensor placement on a bounded 3D sensing field, R, which comprises a number of discrete points that may or may not be grid points. Suppose we have types of se...
This paper presents a novel evolutionary approach to solve numerical optimization problems, called Adaptive Evolution (AEv). AEv is a new micro-population-like technique because i...