Category

Markov models

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stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event

thumb|upright=1.35|An animation of the PageRank algorithm running on a small network of pages. The size of the nodes represents the perceived importance of the page, and arrows represent hyperlinks. thumb|upright=1.35|A simple illustration of the Pagerank algorithm. The percentage shows the perceived importance, and the arrows represent hyperlinks. PageRank (PR) is an algorithm used by Google Search to rank web pages in their search engine results. It is named after both the term "web page" and co-founder Larry Page. PageRank is a way of measuring the importance of website pages. According to

reinforcement learning

type of machine learning where an agent learns how to behave in an environment by performing actions and receiving rewards or penalties in return, aiming to maximize the cumulative reward over time

probabilistic model of a natural or formal language, or generally of elements of signal sequences

snakes and ladders

algorithm that estimates unknowns from a series of measurements over time

hidden Markov model

statistical Markov model

queueing theory

mathematical study of waiting lines, or queues

Markov property

stochastic process satisfying a certain property

stochastic matrix

matrix used to describe the transitions of a Markov chain

Markov chain Monte Carlo

class of algorithms

Viterbi algorithm

multiple sequence alignment

Alignment of more than two molecular sequence

part-of-speech tagging

process of identifying the grammatical type of words in a text

path dependence

actions in the present which are constrained by actions in the past

algorithmic composition

technique of using algorithms to create music

diffusion model

deep learning algorithm

gene prediction

process of identifying the regions of genomic DNA

probability tool

Baum–Welch algorithm

time density of the average information in a stochastic process

detailed balance

Bernoulli scheme

generalization of the Bernoulli process to more than two possible outcomes

forward–backward algorithm

hidden Markov model inference algorithm which computes the posterior marginals of all hidden state variables given a sequence of observations, making use of dynamic programming to make only 2 passes: one forward, one backward

Dynamic Markov compression

Lossless data compression algorithm