Iterated conditional modes
Encyclopedia
In statistics
, iterated conditional modes is a deterministic algorithm
for obtaining the configuration that maximizes the joint probability of a Markov random field. It does this by iteratively maximizing the probability of each variable conditioned
on the rest.
Statistics
Statistics is the study of the collection, organization, analysis, and interpretation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments....
, iterated conditional modes is a deterministic algorithm
Deterministic algorithm
In computer science, a deterministic algorithm is an algorithm which, in informal terms, behaves predictably. Given a particular input, it will always produce the same output, and the underlying machine will always pass through the same sequence of states...
for obtaining the configuration that maximizes the joint probability of a Markov random field. It does this by iteratively maximizing the probability of each variable conditioned
Conditional distribution
Given two jointly distributed random variables X and Y, the conditional probability distribution of Y given X is the probability distribution of Y when X is known to be a particular value...
on the rest.
See also
- Belief propagationBelief propagationBelief propagation is a message passing algorithm for performing inference on graphical models, such as Bayesian networks and Markov random fields. It calculates the marginal distribution for each unobserved node, conditional on any observed nodes...
- Graph cuts in computer visionGraph cuts in computer visionAs applied in the field of computer vision, graph cuts can be employed to efficiently solve a wide variety of low-level computer vision problems , such as image smoothing, the stereo correspondence problem, and many other computer vision problems that can be formulated in terms of energy minimization...
- Optimization problemOptimization problemIn mathematics and computer science, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into two categories depending on whether the variables are continuous or discrete. An optimization problem with discrete...