In this blog, we will summarize the latex code for Probability Formulas and Equations, including Binomial Distribution, Poisson Distribution, Normal Gaussian Distribution, Exponential Distribution, Gamma Distribution, Uniform Distribution, Beta Distribution, Bernoulli Distribution, Geometric Distribution, Beta Binomial Distribution, Poisson Binomial Distribution, Chi-Squared Distribution, Gumbel Distribution, Student t-Distribution, Laplace Distribution, etc. And for multivariate distributions, we will also cover Multinomial Distribution, MultiVariate Normal Distribution, MultiVariate Gamma Distribution, MultiVariate t-Distribution and others.

In this post, we will talk about some real-world applications of deep candidates generation (vector-retrieval) models in the matching stage of recommendation scenario. Commercial recommendation system will recommend tens of millions of items to each user. And the recommendation process usually consists of two stages: The first stage is the candidate generation(matching) stage, a few hundred candidates are selected from the pool of all candidate items. The second stage is the ranking stage in which hundreds of items are ranked and sorted by the ranking score. Then the top rated items are displayed to users.