Exponential family distributions | Multivariate continuous distributions | Continuous distributions | Conjugate prior distributions

Dirichlet distribution

In probability and statistics, the Dirichlet distribution (after Peter Gustav Lejeune Dirichlet), often denoted , is a family of continuous multivariate probability distributions parameterized by a vector of positive reals. It is a multivariate generalization of the beta distribution, hence its alternative name of multivariate beta distribution (MBD). Dirichlet distributions are commonly used as prior distributions in Bayesian statistics, and in fact, the Dirichlet distribution is the conjugate prior of the categorical distribution and multinomial distribution. The infinite-dimensional generalization of the Dirichlet distribution is the Dirichlet process. (Wikipedia).

Dirichlet distribution
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(ML 7.7.A1) Dirichlet distribution

Definition of the Dirichlet distribution, what it looks like, intuition for what the parameters control, and some statistics: mean, mode, and variance.

From playlist Machine Learning

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Value distribution of long Dirichlet polynomials and applications to the Riemann...-Maksym Radziwill

Maksym Radziwill Value distribution of long Dirichlet polynomials and applications to the Riemann zeta-function Stanford University; Member, School of Mathematics October 1, 2013 For more videos, visit http://video.ias.edu

From playlist Mathematics

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(ML 7.8) Dirichlet-Categorical model (part 2)

The Dirichlet distribution is a conjugate prior for the Categorical distribution (i.e. a PMF a finite set). We derive the posterior distribution and the (posterior) predictive distribution under this model.

From playlist Machine Learning

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(ML 7.7) Dirichlet-Categorical model (part 1)

The Dirichlet distribution is a conjugate prior for the Categorical distribution (i.e. a PMF a finite set). We derive the posterior distribution and the (posterior) predictive distribution under this model.

From playlist Machine Learning

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The Normal Distribution (1 of 3: Introductory definition)

More resources available at www.misterwootube.com

From playlist The Normal Distribution

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Dirichlet Eta Function - Integral Representation

Today, we use an integral to derive one of the integral representations for the Dirichlet eta function. This representation is very similar to the Riemann zeta function, which explains why their respective infinite series definition is quite similar (with the eta function being an alte rna

From playlist Integrals

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Statistics: Ch 7 Sample Variability (3 of 14) The Inference of the Sample Distribution

Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn if the number of samples is greater than or equal to 25 then: 1) the distribution of the sample means is a normal distr

From playlist STATISTICS CH 7 SAMPLE VARIABILILTY

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Continuous Distributions: Beta and Dirichlet Distributions

Video Lecture from the course INST 414: Advanced Data Science at UMD's iSchool. Full course information here: http://www.umiacs.umd.edu/~jbg/teaching/INST_414/

From playlist Advanced Data Science

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NOT AS TRIVIAL AS IT MIGHT SEEM! Integrating the Dirichlet Kernel

Help me create more free content! =) https://www.patreon.com/mathable Merch :v - https://teespring.com/de/stores/papaflammy Let us make use of the Dirichlet Kernel today! We are going to integrate this one using its definition as a sum/approximate Fourier Series. Enjoy! My Website: http

From playlist Integrals

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Topic Models: Variational Inference for Latent Dirichlet Allocation (with Xanda Schofield)

This is a single lecture from a course. If you you like the material and want more context (e.g., the lectures that came before), check out the whole course: https://sites.google.com/umd.edu/2021cl1webpage/ (Including homeworks and reading.) Xanda's Webpage: https://www.cs.hmc.edu/~xanda

From playlist Computational Linguistics I

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(ML 8.5) Bayesian Naive Bayes (part 3)

When all the features are categorical, a naïve Bayes classifier can be made fully Bayesian by putting Dirichlet priors on the parameters and (exactly) integrating them out.

From playlist Machine Learning

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Daniel Slonim (Purdue) -- Random Walks in Dirichlet Random Environments on Z with Bounded Jumps

Random walks in random environments (RWRE) are well understood in the one-dimensional nearest-neighbor case. A surprising phenomenon is the existence of models where the walk is transient to the right, but with zero limiting velocity. More difficulties are presented by nearest-neighbor RWR

From playlist Northeastern Probability Seminar 2021

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Why do prime numbers make these spirals? | Dirichlet’s theorem, pi approximations, and more

A curious pattern, approximations for pi, and prime distributions. Help fund future projects: https://www.patreon.com/3blue1brown An equally valuable form of support is to simply share some of the videos. Special thanks to these supporters: http://3b1b.co/spiral-thanks Based on this Math

From playlist Neat proofs/perspectives

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Latent Dirichlet Allocation (Part 1 of 2)

Latent Dirichlet Allocation is a powerful machine learning technique used to sort documents by topic. Learn all about it in this video! This is part 1 of a 2 video series. Video 2: https://www.youtube.com/watch?v=BaM1uiCpj_E For information on my book "Grokking Machine Learning": https:/

From playlist Unsupervised Learning

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Low moments of character sums - Adam Harper

Joint IAS/Princeton University Number Theory Seminar Topic: Low moments of character sums Speaker: Adam Harper Affiliation: University of Warwick Date: April 08, 2021 For more video please visit http://video.ias.edu

From playlist Mathematics

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James Maynard: Half-isolated zeros and zero-density estimates

We introduce a new zero-detecting method which is sensitive to the vertical distribution of zeros of the zeta function. This allows us to show that there are few 'half-isolated' zeros, and allows us to improve the classical zero density result to N(σ,T)≪T24(1−σ)/11+o(1) if we assume that t

From playlist Seminar Series "Harmonic Analysis from the Edge"

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Radek Adamczak: Functional inequalities and concentration of measure III

Concentration inequalities are one of the basic tools of probability and asymptotic geo- metric analysis, underlying the proofs of limit theorems and existential results in high dimensions. Original arguments leading to concentration estimates were based on isoperimetric inequalities, whic

From playlist Winter School on the Interplay between High-Dimensional Geometry and Probability

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May the Convergence be with You - An Exciting Double Integral on the Unit Square

Help me create more free content! =) https://www.patreon.com/mathable Merch :v - https://teespring.com/de/stores/papaflammy https://www.amazon.com/shop/flammablemaths https://shop.spreadshirt.de/papaflammy Eta Int Rep: https://www.youtube.com/watch?v=x

From playlist Integrals

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Exponential family | Grouped Dirichlet distribution | Confluent hypergeometric function | Lebesgue measure | Beta distribution | Mode (statistics) | Moment (mathematics) | Support (mathematics) | Matrix variate Dirichlet distribution | Concentration parameter | Conjugate prior | Gamma distribution | Lauricella hypergeometric series | Rényi entropy | Statistics | Probability density function | Pólya urn model | Probability | Kronecker delta | Multivariate random variable | Trigamma function | Differential entropy | Latent Dirichlet allocation | Dirichlet process | Independence (probability theory) | Marginal distribution | Bayesian statistics | Hyperprior | Digamma function | Dirichlet-multinomial distribution | Martingale (probability theory) | Bayesian inference | Equilateral triangle | Peter Gustav Lejeune Dirichlet | Simplex | Statistical inference | Mixture model | Inverted Dirichlet distribution | Gamma function | Generalized Dirichlet distribution | Integer | Vector (mathematics and physics) | Real number | Multinomial distribution | Probability distribution | Euclidean space | Random variate | Scalar (mathematics) | Beta function | Gibbs sampling | Random variable | Normalizing constant | Binomial distribution | Nat (unit) | Triangle | Categorical distribution | Bernoulli distribution | Invertible matrix | Open set