Add to ORKGWe examine several methods for drawing a sequential random sample of n records from a file containing N records. Method D, which was introduced in [10], is recommended for general use. The algorithm is online (so that CPU time can be overlapped with I/O), has a small constant memory requirement, and is easy to program. An improved implementation is given in the Appendix
International audienceWe tackle the feasibility and efficiency of two new parallel algorithms that s...
The existing random sampling methods have at least one of the following disadvantages: they 1) are a...
I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, ...
We analyze a standard algorithm for sampling m items without replacement from a computer file of n r...
In this lecture, we will discuss a fundamental problem: given a set S of size n, how to obtain a ran...
Sequential sampling algorithms have recently attracted interest as a way to design scalable algorith...
Sequential sampling algorithms have recently attracted interest as a way to design scalable algorith...
We study the fundamental problem of the exact and efficient generation of random values from a finit...
Many data acquisition systems incorporate high-speed scanners to convert analog signals into digital...
Abstract. Random sampling is a well-known technique for approximate processing of large datasets. We...
Random sampling is a well-known technique for approximate processing of large datasets. We introduce...
In this paper we show the power of sampling techniques in designing efficient distributed algorithms...
International audienceThe seminal works of Wilf and Nijenhuis in the late 70s have led to efficient ...
The paper studies the optimal sequential sampling policy of the partitioned random search (PRS) and ...
AbstractA sequential sampling algorithm or adaptive sampling algorithm is a sampling algorithm that ...
International audienceWe tackle the feasibility and efficiency of two new parallel algorithms that s...
The existing random sampling methods have at least one of the following disadvantages: they 1) are a...
I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, ...
We analyze a standard algorithm for sampling m items without replacement from a computer file of n r...
In this lecture, we will discuss a fundamental problem: given a set S of size n, how to obtain a ran...
Sequential sampling algorithms have recently attracted interest as a way to design scalable algorith...
Sequential sampling algorithms have recently attracted interest as a way to design scalable algorith...
We study the fundamental problem of the exact and efficient generation of random values from a finit...
Many data acquisition systems incorporate high-speed scanners to convert analog signals into digital...
Abstract. Random sampling is a well-known technique for approximate processing of large datasets. We...
Random sampling is a well-known technique for approximate processing of large datasets. We introduce...
In this paper we show the power of sampling techniques in designing efficient distributed algorithms...
International audienceThe seminal works of Wilf and Nijenhuis in the late 70s have led to efficient ...
The paper studies the optimal sequential sampling policy of the partitioned random search (PRS) and ...
AbstractA sequential sampling algorithm or adaptive sampling algorithm is a sampling algorithm that ...
International audienceWe tackle the feasibility and efficiency of two new parallel algorithms that s...
The existing random sampling methods have at least one of the following disadvantages: they 1) are a...
I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, ...