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Reservoir sampling

Reservoir sampling is a family of randomized algorithms for randomly choosing a sample of k items from a list S containing n items, where n is either… 
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Broader (1)

Analysis of algorithms
Fisher–Yates shuffleMathematical inductionOnline algorithmPython

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Scalable Reservoir Sampling on Many-Core CPUs
Database systems need to be able to convert queries to efficient execution plans. As recent research has shown, correctly… 
2017
2017
SILVERBACK+: scalable association mining via fast list intersection for columnar social data
We present Silverback+, a scalable probabilistic framework for accurate association rule and frequent item-set mining of large… 
2016
2016
Bayesian Network Structure Learning from Big Data: A Reservoir Sampling Based Ensemble Method
Bayesian network (BN) learning from big datasets is potentially more valuable than learning from conventional small datasets as… 
2014
2014
Optimization issues of querying and evolving sensor and stream databases
2012
2012
Sampling methods for summarizing unordered vehicle-to-vehicle data streams
Review
2012
Review
2012
Reservoir sampling techniques in modern data analysis
Reservoir sampling is an interesting statistical sampling technique, developed almost 40 years ago in order to enable analysis of… 
2007
2007
Random Sampling over Data Streams for Sequential Pattern Mining
, 
2007
2007
Reservoir Sampling over Memory-Limited Stream Joins
In stream join processing with limited memory, uniform random sampling is useful for approximate query evaluation. In this paper… 
2006
2006
Sequential reservoir sampling with a nonuniform distribution
We present a simple algorithm that allows sampling from a stream of data items without knowing the number of items in advance and… 
2005
2005
Density-biased clustering based on reservoir sampling
Clustering is a task of grouping data based on similarity. A popular k-means algorithm groups data by firstly assigning all data… 
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