Big Data on the Rise? - Testing Monotonicity of Distributions
Big Data on the Rise? - Testing Monotonicity of Distributions
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大数据正在崛起？
DOI：
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发表时间：
2015
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通讯作者：
C. Canonne
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文献类型：
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作者：
C. Canonne
概率分布或发行测试的属性测试领域旨在为与非常大的数据集有关的特定方面的问题提供快速且（最有可能）正确的答案。在这项工作中，我们考虑了具有特殊关注的属性，即分布的单调性。我们专注于跨不同访问分布的不同模型的单调性测试的复杂性[5,7,8,20]；并在这些新设置中获得结果，这些新设置与标准采样模型中的已知界限显着不同（有些令人惊讶）[1]。
The field of property testing of probability distributions, or distribution testing, aims to provide fast and (most likely) correct answers to questions pertaining to specific aspects of very large datasets. In this work, we consider a property of particular interest, monotonicity of distributions. We focus on the complexity of monotonicity testing across different models of access to the distributions [5, 7, 8, 20]; and obtain results in these new settings that differ significantly (and somewhat surprisingly) from the known bounds in the standard sampling model [1].