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相关概念视频

Cluster Sampling Method01:20

Cluster Sampling Method

12.7K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Stratified Sampling Method01:16

Stratified Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
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Sampling Plans01:23

Sampling Plans

258
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
258
Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
12.3K
Systematic Sampling Method01:17

Systematic Sampling Method

11.1K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
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Sampling Methods: Overview01:06

Sampling Methods: Overview

498
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
498

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An Unbiased Approach of Sampling TEM Sections in Neuroscience
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联合半监督学习与统一的随机和基于格子的客户端抽样

Mei Zhang1, Feng Yang2

  • 1School of Mathematics, Southwest Minzu University, Chengdu 610225, China.

Entropy (Basel, Switzerland)
|August 28, 2025
PubMed
概括

联邦半监督学习 (Fed-SSL) 从结构化抽样策略中获益. 在FedAvg-SSL中基于格子的采样提高了非ID的训练稳定性和性能. 与随机方法相比的数据.

科学领域:

  • 人工智能
  • 机器学习
  • 分布式系统

背景情况:

  • 联合半监督学习 (Fed-SSL) 使用分布式标记和未标记的数据.
  • 在Fed-SSL中,部分客户参与是常见的,以减少通信开销.
  • 没有识别 在Fed-SSL中,数据分布对客户采样策略构成挑战.

研究的目的:

  • 提出一个新的联合平均半监督学习算法,FedAvg-SSL.
  • 调查不同客户抽样策略对Fed-SSL业绩的影响.
  • 分析拟议算法的收性质.

主要方法:

  • 引入了FedAvg-SSL,包括统一的随机抽样 (蒙特卡洛) 和基于格子的抽样 (准蒙特卡洛).
  • 客户在更新全球模型和使用本地数据改进伪标签模型之间交替.
  • 提供理论的融合分析,并进行了广泛的实验.

主要成果:

  • 通过FedAvg-SSL实现了线性加速的次线性融合率.
  • 基于格子的抽样在联合学习中比统一的随机抽样具有优势.
  • 实验结果验证了理论发现,并突出了采样策略的影响.
关键词:
收率联合的半监督学习线性加速部分客户参与准蒙特卡洛技术

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结论:

  • FedAvg-SSL提供了一个有效的联合半监督学习方法.
  • 基于格子的采样增强了训练稳定性和模型性能,特别是在非i.i.d下. 这种情况.
  • 这项研究为优化客户参与和采样提供了洞察力.