Reservoir sampling is a known technique for maintaining a random sample of a fixed size over a data stream of an unknown size. While reservoir sampling is suitable for applications demanding a sample over the whole data stream, it is not designed for ...
Sampling is a process of choosing a suitable representative subset from a population and uniformity is a basic requirement of representative ness. A sampling process produces a uniform random sample when all possible samples of the same size have the ...
Gaining knowledge out of vast datasets is a main challenge in data-driven applications nowadays. Sparse grids provide a numerical method for both classification and regression in data mining which scales only linearly in the number of data points and is ...
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