A Statistical Analysis of Probabilistic Counting Algorithms

Probabilistic Counting Algorithms for Data Base Applications

A Statistical-Probabilistic Pattern for Determination of Tunnel Advance Step by Quantitative Risk Analysis

One of the main challenges faced in design and construction phases of tunneling projects is the determination of maximum allowable advance step to maximize excavation rate and reduce project delivery time. Considering the complexity of determining this factor and unexpected risks associated with inappropriate determination of that, it is necessary to employ a method which is capable of accounti...

Analysis of a splitting process arising in probabilistic counting and other related algorithms

Wojciech S:r,pankowskit Dept. Computer Science Purdue University W. Lafayette, IN 47907 U.S.A. vVe present an analytical method of analyzing a class of "splitting algorilhms" that include probabilistic counting, selecting the leader, estimating the number of questions necessary to identify distinct objects, searching algorithms based on digital tries, approximate counting, ,mel so forth. In our...

Probabilistic Analysis of Algorithms

Rather than analyzing the worst case performance of algorithms, one can investigate their performance on typical instances of a given size. This is the approach we investigate in this paper. Of course, the first question we must answer is: what do we mean by a typical instance of a given size? Sometimes, there is a natural answer to this question. For example, in developing an algorithm which i...

A Probabilistic Counting Algorithm

This talk1 (a joint work with Philippe Flajolet) presents an algorithm to approximate count the number of different words in very large sets or texts (in the range of billions of bytes) and its analysis. When using an auxiliary memory of m bytes, the accuracy is of the order 1/ √ m. The analysis of this new algorithm relies on asymptotic Depoissonization techniques.