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相关概念视频

Probability Distributions01:32

Probability Distributions

7.2K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
7.2K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.5K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.5K
Uniform Distribution01:19

Uniform Distribution

5.1K
The uniform distribution is a continuous probability distribution of events with an equal probability of occurrence. This distribution is rectangular.
Two essential properties of this distribution are
5.1K
F Distribution01:19

F Distribution

3.7K
The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
3.7K
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.1K
The Anderson-Darling Test01:16

The Anderson-Darling Test

757
The Anderson-Darling test is a statistical method used to determine whether a data sample is likely drawn from a specific theoretical distribution. Unlike parametric tests, it does not require assumptions about specific parameters of the distribution. Instead, it compares the sample's empirical cumulative distribution function (ECDF) with the cumulative distribution function (CDF) of the hypothesized distribution. Critical values for the test are specific to the chosen distribution rather...
757

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相关实验视频

Updated: Jul 16, 2025

The Diffusion of Passive Tracers in Laminar Shear Flow
08:01

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

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分布不变的差异性隐私保护

Xuan Bi1, Xiaotong Shen2

  • 1Information and Decision Sciences, Carlson School of Management, University of Minnesota, Minneapolis, MN.

Journal of econometrics
|September 13, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了一种名为分布不变私有化 (DIP) 的新方法,以保护数据隐私而不牺牲准确性. DIP确保数据分析结论保持一致,平衡隐私和统计完整性.

关键词:
隐私保护 隐私保护 隐私保护数据干扰的数据干扰.分享数据的数据共享.分布 保存 保存 保存随机化机制是随机化的机制.

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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相关实验视频

Last Updated: Jul 16, 2025

The Diffusion of Passive Tracers in Laminar Shear Flow
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The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

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Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

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科学领域:

  • 数据隐私 数据隐私
  • 统计分析 统计分析
  • 机器学习是机器学习.

背景情况:

  • 差异隐私是保护共享数据的标准,用于各种领域.
  • 现有的方法面临隐私和统计准确性之间的权衡,可能会改变分析结论.
  • 这种权衡是因为隐私的改变会改变数据的分布.

研究的目的:

  • 为了减轻数据共享中的隐私-实用性权衡.
  • 开发一种新的方法,确保严格的差异隐私和高统计准确性.
  • 为了使下游分析能够得出与原始非私人数据一致的结论.

主要方法:

  • 引入了一种新的分配不变私有化 (DIP) 方法.
  • 设计DIP,在隐私增强过程中保留底层数据分布.
  • 评估了DIP与模拟和现实场景中的现有方法的性能.

主要成果:

  • DIP成功地将严格的差异隐私与高统计准确度相结合.
  • 该方法确保私有化数据分析的结论与原始数据的结论一致.
  • 与同等隐私保证下的现有方法相比,DIP显示出更高的统计准确性.

结论:

  • 开发的分布不变私有化 (DIP) 方法有效地解决了隐私-实用性权衡问题.
  • DIP提供了一个强大的解决方案,用于共享敏感数据,同时保持分析完整性.
  • 这种方法推进了数据科学和其他领域的差异性隐私的应用.