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相关概念视频

Probability Distributions01:32

Probability Distributions

6.8K
 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...
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Probability in Statistics01:14

Probability in Statistics

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Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
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Uniform Distribution01:19

Uniform Distribution

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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
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
107
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.0K
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...
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Binomial Probability Distribution01:15

Binomial Probability Distribution

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A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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关于质量分布的机器学习

Alexander Kolpakov1, A Alistair Rocke2

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科学领域:

  • 数学理论 数学理论
  • 可能性理论概率理论.
  • 机器学习理论机器学习理论

背景情况:

  • 哈迪 - 拉马努贾定理描述了加法数理论函数的分布.
  • 了解素数的可学习性对于理论计算机科学至关重要.
  • 埃尔多斯-卡克定律涉及整数质因子的分布.

研究的目的:

  • 使用最大的方法,在概率数论中推导出新的定理.
  • 为了提供理论解释观察到的现象在质数学习能力.
  • 评估使用当代机器学习算法发现埃尔多斯-卡克定律的可能性.

主要方法:

  • 应用最大的方法来推导定理.
  • 对素数学习能力的理论分析.
  • 理论发现与机器学习能力的比较分析.

主要成果:

  • 几定理在概率数论的衍生,包括一个新的版本的哈迪-拉曼努安定理.
  • 建立了一个理论框架来解释实验观察到的初级可学习性.
  • 确定埃尔多斯-卡克定律不太可能通过当前的机器学习技术被发现.

结论:

  • 最大的方法是有效的推进概率数论.
  • 原数的可学习性有一个理论基础,当前的人工智能可能无法很容易地发现.
  • 突出了机器学习在发现像埃尔多斯-卡克定律这样的基本数学定律方面的局限性.