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- Concentration_inequality abstract "In mathematics, concentration inequalities provide probability bounds on how a random variable deviates from some value (e.g. its expectation). The laws of large numbers of classical probability theory state that sums of independent random variables are, under very mild conditions, close to their expectation with a large probability. Such sums are the most basic examples of random variables concentrated around their mean. Recent results shows that such behavior is shared by other functions of independent random variables.".
- Concentration_inequality wikiPageID "32023963".
- Concentration_inequality wikiPageRevisionID "595919348".
- Concentration_inequality hasPhotoCollection Concentration_inequality.
- Concentration_inequality subject Category:Inequality.
- Concentration_inequality comment "In mathematics, concentration inequalities provide probability bounds on how a random variable deviates from some value (e.g. its expectation). The laws of large numbers of classical probability theory state that sums of independent random variables are, under very mild conditions, close to their expectation with a large probability. Such sums are the most basic examples of random variables concentrated around their mean.".
- Concentration_inequality label "Concentration inequality".
- Concentration_inequality label "集中不等式".
- Concentration_inequality sameAs m.0gx2rfg.
- Concentration_inequality sameAs Q5158328.
- Concentration_inequality sameAs Q5158328.
- Concentration_inequality wasDerivedFrom Concentration_inequality?oldid=595919348.
- Concentration_inequality isPrimaryTopicOf Concentration_inequality.