Examples of using Markov in English and their translations into Chinese
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Political
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Ecclesiastic
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Programming
Specific topics include machine learning, search, game playing, Markov decision processes, constraint satisfaction, graphical models, and logic.
Markov emigrated to the U.S. with his parents and received his United States citizenship in 1982.
Markov models are an example of reinforcement learning, and self-driving autonomous automobiles are a great example of just such an application.
Pandora's features are handcrafted, but in Markov networks we can also learn features using hill climbing, similar to rule induction.
Tara Markov is a young lady who has control over earth and stone; she is likewise more than she appears.
The result of Markov analysis is a mapping from each prex(like half the and the bee) to all possible sufxes(like has and is).
Partially observable markov decision processes(POMDP), reinforcement learning, multi-agent systems.
Markov's musical journey goes beyond his work as a classical violin soloist.
The minimum acceptable recovery time is determined using technique such as Markov process analysis[27] or stochastic activity network simulation[28].
But for a Markov chain one is usually more interested in a stationary state that is the limit of the sequence of distributions for some initial distribution.
Defendants Markov, Todorov, Stoytchev, Hristov and Dimitrovgrad had all been indicted under various charges in connection with the case(26 February 1998).
Hidden Markov Models were first described in a series of statistical papers by Leonard E.
Markov said Echelon is a private and independent company, but it does have a business relationship with Russia's military and law enforcement authorities.
Jared Markov discovered the first of these ruins centuries ago, on a planet over a hundred light-years distant from this spot.
Chapter 3~5 describe three fundamental classes of methods for solving finite Markov decision problems: dynamic programming, Monte Carlo methods, and temporal-difference learning.
Markov networks are a staple in many areas, such as computer vision.
He uses Markov decision processes, reinforcement learning and artificial intelligence methods to understand the impact of market irrationality on trading, portfolio and systemic risk.
Using Markov analysis to generate random text is fun, but there is also a point to this exercise: data structure selection.
Probability and statistic functions, that vary from statistical distributions and calculating descriptive statistics(such as mean, variance and standard deviation) to Markov chain models.
So Markov logic includes both logic and Markov networks as special cases, and it's the unification we were looking for.