Test Results of Variance Reduction Techniques Applied to Deep Penetration Problem

Variance Reduction Techniques in . . .

Variance Reduction Techniques in Monte Carlo Methods

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the introduction of computers. This increased computer power has stimulated simulation analysts to develo...

A Review on Deep Learning Techniques Applied to Semantic Segmentation

Image semantic segmentation is more and more being of interest for computer vision and machine learning researchers. Many applications on the rise need accurate and efficient segmentation mechanisms: autonomous driving, indoor navigation, and even virtual or augmented reality systems to name a few. This demand coincides with the rise of deep learning approaches in almost every field or applicat...

Test Case Reduction Techniques - Survey

Regression testing is considered to be the most expensive phase in software testing. Therefore, regression testing reduction eliminates the redundant test cases in the regression testing suite and saves cost of this phase. In order to validate the correctness of the new version software project that resulted from maintenance phase, Regression testing reruns the regression testing suite to ensur...

Data Mining Techniques Applied to Hydrogen Lactose Breath Test

OBJECTIVES Analyze a set of data of hydrogen breath tests by use of data mining tools. Identify new patterns of H2 production. METHODS Hydrogen breath tests data sets as well as k-means clustering as the data mining technique to a dataset of 2571 patients. RESULTS Six different patterns have been extracted upon analysis of the hydrogen breath test data. We have also shown the relevance of e...