We present a split-and-merge expectation-maximization (SMEM) algorithm to overcome the local maxima problem in parameter estimation of finite mixture models. In the case of mixture models, local maxima often involve having too many components of a mixture model in one part of the space and too few in another, widely separated part of the space. To escape from such configurations, we repeatedly ...

Image Registration is the process of determining a transform that provides the most accurate match between two images. The search for matching transformation can be automated with the use of suitable metric, but it is difficult to determine local maxima with direct search methods. In this paper a simple and powerful search strategy based on genetic algorithm is proposed to register satellite im...

EM training of GMM often suffers from the existence of local maxima and singularities in the likelihood space. In this paper, we present a new Modified Split-and-Merge EM algorithm (MSMEM) for speaker verification tasks, which performs split-and-merge operations to escape from local maxima and reduce the chances of generating singularities. With two modified criteria to select split-and-merge c...

We present an algorithm to overcome the local maxima problem in estimating the parameters of mixture models. It combines existing approaches from both EM and a robust fitting algorithm, RANSAC, to give a data-driven stochastic learning scheme. Minimal subsets of data points, sufficient to constrain the parameters of the model, are drawn from proposal densities to discover new regions of high li...

Continual improvement of oxygenators has been important in the growing demands of patient safety and support during cardiopulmonary bypass. The purpose of this study was to compare the Maxima 1380 oxygenator to the upgraded Maxima Plus oxygenator. Thirty-two adult patients were randomized to either the 1380 group or the Plus group. Information was recorded on the patients' weight, age, body sur...

In this paper we propose a new 3D kernel for the recovery of 3Dorientation signatures. The kernel is a Gaussian function defined in local spherical coordinates and its Cartesian support has the shape of a truncated cone with axis in radial direction and very small angular support. A set of such kernels is obtained by uniformly sampling the 2D space of polar and azimuth angles. The projection of...

substantiation of the averaging method for differential equations with maxima is presented. two theorems on substantiates for differential equations with maxima are established.

We propose a new 3D kernel for the recovery of 3D orientation signatures. In the Cartesian coordinates, the kernel has a shape of a truncated cone with its axis in the radial direction and very small angular support. In the local spherical coordinates, the angular part of the kernel is a 2D Gaussian function. A set of such kernels is obtained by uniformly sampling the 2D space of azimuth and el...

The discovery of regulatory networks is an important aspect in the post genomic research. Among structure learning approaches we are interested in local search methods in the Bayesian network framework. We propose a new local move operator to escape more efficiently from local maxima in the search space of directed acyclic graphs. This operator allows to overtake the acyclic constraint of Bayes...

An electromagnetic study of the staircase approximation of arbitrary shaped gratings is conducted with three different grating theories. Numerical results on a deep aluminum sinusoidal grating show that the staircase approximation introduces sharp maxima in the local field map close to the edges of the profile. These maxima are especially pronounced in TM polarization and do not exist with the ...