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Bennett's inequality, an upper bound on the probability that the sum of independent random variables deviates from its expected value by more than any specified amount Bhatia–Davis inequality , an upper bound on the variance of any bounded probability distribution
The feasible regions of linear programming are defined by a set of inequalities. In mathematics, an inequality is a relation which makes a non-equal comparison between two numbers or other mathematical expressions. [1] It is used most often to compare two numbers on the number line by their size.
In mathematics, an inequation is a statement that an inequality holds between two values. [1] [2] It is usually written in the form of a pair of expressions denoting the values in question, with a relational sign between them indicating the specific inequality relation. Some examples of inequations are:
Ladyzhenskaya's inequality; Landau–Kolmogorov inequality; Landau-Mignotte bound; Lebedev–Milin inequality; Leggett inequality; Leggett–Garg inequality; Less-than sign; Levinson's inequality; Lieb–Oxford inequality; Lieb–Thirring inequality; Littlewood's 4/3 inequality; Log sum inequality; Łojasiewicz inequality; Lubell–Yamamoto ...
Two-dimensional linear inequalities are expressions in two variables of the form: + < +, where the inequalities may either be strict or not. The solution set of such an inequality can be graphically represented by a half-plane (all the points on one "side" of a fixed line) in the Euclidean plane. [2]
In mathematics, Clarkson's inequalities, named after James A. Clarkson, are results in the theory of L p spaces. They give bounds for the L p - norms of the sum and difference of two measurable functions in L p in terms of the L p -norms of those functions individually.
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