subgaussian distribution are dominated by (i.e. decay at least as fast as) the tails of a Gaussian. This property gives subgaussian distributions their name...

theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable...

inequality can be generalized to any sub-Gaussian distribution. Recall that a random variable X is called sub-Gaussian, if P ( | X | ≥ t ) ≤ 2 e − c t 2...

distribution Modified half-normal distribution Sub-Gaussian distribution Laurenson, Dave (1994). "Nakagami Distribution". Indoor Radio Channel Propagation...

probability that the empirical risk deviates from the true risk to be a Sub-Gaussian distribution. P ( | R ^ ( f ) − R ( f ) | ≥ ϵ ) ≤ 2 e − 2 n ϵ 2 {\displaystyle...

identify the sub-population to which an individual observation belongs. Formally a mixture model corresponds to the mixture distribution that represents...

-1/K\leq \lambda \leq 1/K} . | X | {\displaystyle {\sqrt {|X|}}} is sub-Gaussian. High-Dimensional Probability: An Introduction with Applications in Data...

signifies a leptokurtic distribution. The Laplace distribution, for example, has tails that decay more slowly than a Gaussian, resulting in more outliers...

sum of these individual plane-wave contributions will exhibit a Gaussian distribution. This type of GRF is completely described by its power spectral...

Distributions, also known as Schwartz distributions are a kind of generalized function in mathematical analysis. Distributions make it possible to differentiate...

and the generalized inverse Gaussian distribution. Among the discrete distributions, the negative binomial distribution is sometimes considered the discrete...

_{i=1}^{k}{\frac {(x_{i}-np_{i})^{2}}{np_{i}}}} This resembles the gaussian distribution, which suggests the following theorem: Theorem. At the n → ∞ {\displaystyle...

Andreas; Pontil, Pontil (2021). "Concentration inequalities under sub-Gaussian and sub-exponential conditions" (PDF). Advances in Neural Information Processing...

equilibrium, unlike the final distribution. The equilibrium distribution is the Gaussian distribution N ( 0 , I ) {\displaystyle {\mathcal {N}}(0,I)} , with...

proposal function, or jumping distribution. A common choice for g ( x ∣ y ) {\displaystyle g(x\mid y)} is a Gaussian distribution centered at y {\displaystyle...

number of distributions, ω is a weight associated to the ith Gaussian at time t and μ, Σ are the mean and standard deviation of said Gaussian respectively...

the sample size. This approximation is termed the normal distribution approximation, Gaussian approximation, or Silverman's rule of thumb. While this rule...

Bilinear time–frequency distributions, or quadratic time–frequency distributions, arise in a sub-field of signal analysis and signal processing called...

The Oxford Dictionary of English Etymology, Oxford English Dictionary, sub "mathematics", "mathematic", "mathematics". "Maths (Noun)". Oxford English...

scale t {\displaystyle t} . The main type of scale space is the linear (Gaussian) scale space, which has wide applicability as well as the attractive property...

generalizations. Gaussian belief propagation is a variant of the belief propagation algorithm when the underlying distributions are Gaussian. The first work...

Limit Theorem, the distribution of a sum of independent random variables with finite variance tends towards a Gaussian distribution. Loosely speaking,...

volatility is high, the optimization of portfolios when return distributions are non-Gaussian is mathematically challenging. Hierarchical Risk Parity is a...

{\displaystyle N} a random walker has a Gaussian probability distribution. Thus, the joint probability distribution for the real and imaginary parts of the...

certain theorem valid for all regions of acceptability and all Gaussian distributions. The efficiency of NA relies on information theory and a certain...

space with respect to a given probability distribution. More specifically, the expected supremum of a sub-gaussian process is bounded up to finite constants...

random variables, including convergence in probability, convergence in distribution, and almost sure convergence. The different notions of convergence capture...

Exponentiating by squaring Exponentiation Fermat's Last Theorem Forgetting curve Gaussian function Gudermannian function Half-exponential function Half-life Hyperbolic...

choosing a different distribution from where the samples are chosen, for instance by sampling according to a gaussian distribution centered at 0, with...

extrapolate to T(0). Gaussian quadrature evaluates the function at the roots of a set of orthogonal polynomials. An n-point Gaussian method is exact for...