IBM Model 1 is a classical alignment model. Of the first generation word-based SMT models, it was the only such model with a concave objective function. For concave optimization problems like IBM Model 1, we have guarantees on the convergence of optimization algorithms such as Expectation Maximization (EM). However, as was pointed out recently, the objective of IBM Model 1 is not strictly conca...

Color nonstandardness--the propensity for similar objects to exhibit different color properties across images--poses a significant problem in the computerized analysis of histopathology. Though many papers propose means for improving color constancy, the vast majority assume image formation via reflective light instead of light transmission as in microscopy, and thus are inappropriate for histo...

IBM Model 1 is a classical alignment model. Of the first generation word-based SMT models, it was the only such model with a concave objective function. For concave optimization problems like IBM Model 1, we have guarantees on the convergence of optimization algorithms such as Expectation Maximization (EM). However, as was pointed out recently, the objective of IBM Model 1 is not strictly conca...

Due to random deployment of static sensor nodes and environmental factors existence of holes in wireless sensor networks is inevitable. This holes results in reducing the data transmission performance and in additional energy consumption. Consequently, the hole problem is an important factor for prolonging the network lifetime. The network lifetime can be improved by deploying additional mobile...

We emphasize the need for input-dependent regularization in the context of conditional density models (also: discriminative models) like Gaussian process predictors. This can be achieved by a simple modification of the standard Bayesian data generation model underlying these techniques. Specifically, we allow the latent target function to be apriori dependent on the distribution of the input po...

Inference of network internal link characteristics has become an increasingly important issue for network monitor and network management. In this paper, an improved EM algorithm based on A* algorithm was proposed for network link delay distributions inference. We use A* algorithm to accelerate the convergence speed of EM algorithm. Experiment results show the improved EM algorithm is faster tha...

Average case performance of the deterministic annealing EM algorithm is evaluated for Gaussian mixture estimation problem under some additive noises. The data-averaged EM update equations with respect to hyperparameters are calculated analytically in the large data limit. We find that the EM algorithm strongly depends on the initial conditions. Moreover, by using our analysis, it becomes possib...

Fixed charge solid transportation problem (FCSTP) is one of the main and most important problems in transportation and network research areas. To tackle such an NP-hard problem, An Electromagnetism-like algorithm (EM) is employed. To the best of our knowledge, EM has been considered for any kind of transportation problems. Due to the significant role of parameters on the algorithm’s performance...

Segmentation of anatomical regions of brain is fundamental problem in medical image analysis. In general, segmentation is process in which object is divided into its constituents parts. In this paper, MRI of brain is divided into its constituent’s parts which may be used for medical diagnosis purpose. Consequently we used statistical approach to segment the brain image. Using this approach, we ...

the relation between single nucleotide polymorphisms (snps) and some diseases has been concerned by many researchers. also the missing snps are quite common in genetic association studies. hence, this article investigates the relation between existing snps in dnmt1 of human chromosome 19 with colorectal cancer. this article aims is to presents an imputation method for missing snps not at random...