Monte Carlo simulation methods apply a random sampling and modifications can be made of this method is by using variance reduction techniques (VRT). VRT objective is to reduce the variance due to Monte Carlo methods become more accurate with a variance approaching zero and the number of samples approaches infinity, which is not practical in the real situation (Chen, 2004). These techniques are ...

Scaling up data mining algorithms to handle huge data sets is an important issue in machine learning and knowledge discovery. Random sampling is often used to achieve better scalability in learning from massive amount of data. Adaptive sampling offers advantages over traditional batch sampling methods in that adaptive sampling often uses much lower number of samples and thus better efficiency w...

Abstract Multiphoton interference is an essential phenomenon at the very heart not only of fundamental quantum optics and applications in information processing sensing but also demonstrations computational supremacy boson sampling experiments relying on linear optical interferometers. However, scalable with either photon number states or squeezed are challenged by need to generate a large phot...

When estimating how much better a classifier is than random allocation in Q-class ROC analysis, we need to sample from a particular region of the unit hypercube: specifically the region, in the unit hypercube, which lies between the Q− 1 simplex in Q(Q− 1) space and the origin. This report introduces a fast method for randomly sampling this volume, and is compared to rejection sampling of unifo...

In this work we present a simple and efficient algorithm which, with high probability, provides an almost uniform sample from the set of proper k-colourings on an instance of sparse random graphs Gn,d/n, where k = k(d) is a sufficiently large constant. Our algorithm is not based on the Markov Chain Monte Carlo method (M.C.M.C.). Instead, we provide a novel proof of correctness of our Algorithm ...

The latin hypercube sampling method, which represents the most efficient way to determine the statistics of the creep and shrinkage response of structures, has previously been developed and used under the assumption that the random parameters of the creep and shrinkage prediction model are mutually independent. In reality they are correlated. On the basis of existing data, this paper establishe...