Examples of using Dynamic programming in English and their translations into Russian
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This special structure allows the discrete Fréchet distance to be computed in polynomial time by an easy dynamic programming algorithm.
such as dynamic programming and divide-and-conquer.
Many algorithmic problems that are NP-complete for arbitrary graphs may be solved efficiently for partial k-trees by dynamic programming, using the tree decompositions of these graphs.
such as branch and bound and dynamic programming.
Path decomposition may also be used to measure the space complexity of dynamic programming algorithms on graphs of bounded treewidth.
are closely related to treewidth and form the basis for efficient dynamic programming algorithms on graphs.
For graphs of bounded clique-width, the longest path can also be solved by a polynomial time dynamic programming algorithm.
when an efficient algorithm based on dynamic programming was published.
By the time he retired, he had published over 90 books and papers on dynamic programming, game theory,
This dynamic programming approach is used in machine learning via the junction tree algorithm for belief propagation in graphs of bounded treewidth.
are therefore often solved using dynamic programming.
can be found using dynamic programming, again in linear time.
As a consequence, by Courcelle's theorem, efficient dynamic programming algorithms exist for many problems on these graphs.
of sequence alignment and Nussinov(maximal-pairing) folding dynamic programming method.
Many optimization problems that are NP-hard for more general classes of graphs may be solved efficiently by dynamic programming on graphs of bounded clique-width,
As for university education, competitions help students learn more about dynamic programming, string algorithms,
The term dynamic programming was originally used in the 1940s by Richard Bellman to describe the process of solving problems where one needs to find the best decisions one after another.
The problem can be solved using dynamic programming when the size of the set
the maximum independent set itself can be found(as is standard in dynamic programming algorithms) by backtracking through these stored values starting from this largest value.
branch-decomposition of this graph, and applying dynamic programming to the decomposition.