동적 계획법

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노트

  • In this paper we investigate systolic processing for problems formulated in dynamic programming.[1]
  • Dynamic Programming refers to a very large class of algorithms.[2]
  • Dynamic programming is an algorithmic technique that is closely related to the divide and conquer approach we saw in the previous chapter.[3]
  • Dynamic programming involves breaking down significant programming problems into smaller subsets and creating individual solutions.[4]
  • There are two different approaches to store computed values in dynamic programming, namely, Memoization and Tabulation.[5]
  • (MAP) inference is found exactly using dynamic programming.[6]
  • Dynamic programming is a general technique for solving optimization, search and counting problems that can be decomposed into subproblems.[7]
  • Conceptually dynamic programming involves recursion.[7]
  • Optimal substructure and overlapping subproblems are the two attributes a problem must have to be solved used dynamic programming.[7]
  • Let’s try to get a feel for what kind of problems can be solved using dynamic programming.[7]
  • The method of dynamic programming was first proposed by Bellman.[8]
  • I’ve been helping a friend understand dynamic programming (DP for short), so I’ve been on the lookout for good resources.[9]
  • Dynamic programming helps us solve recursive problems with a highly-overlapping subproblem structure.[9]
  • Computationally, dynamic programming boils down to write once, share and read many times.[10]
  • If a problem doesn't have overlapping sub problems, we don't have anything to gain by using dynamic programming.[11]
  • Dynamic Programming (DP) is a bottom-up approach to problem solving where one sub-problem is solved only once.[12]
  • When it comes to Dynamic programming, perhaps the best check is to investigate for optimal substructure and overlapping sub-problems.[12]
  • Dynamic programming is mostly applied to recursive algorithms.[13]
  • But not all problems that use recursion can use Dynamic Programming.[13]
  • Bellman named it Dynamic Programming because at the time, RAND (his employer), disliked mathematical research and didn't want to fund it.[14]
  • An interesting question is, Where did the name, dynamic programming, come from?[14]
  • Thus, I thought dynamic programming was a good name.[14]
  • This is a small example but it illustrates the beauty of Dynamic Programming well.[14]
  • Dynamic programming is used where we have problems, which can be divided into similar sub-problems, so that their results can be re-used.[15]
  • Dynamic programming can be used in both top-down and bottom-up manner.[15]
  • Wherever we see a recursive solution that has repeated calls for same inputs, we can optimize it using Dynamic Programming.[16]
  • During my algorithms class this year, I pieced together my own process for solving problems that require dynamic programming.[17]
  • In dynamic programming, after you solve each sub-problem, you must memoize, or store it.[17]
  • Working through Steps 1 and 2 is the most difficult part of dynamic programming.[17]
  • One final piece of wisdom: keep practicing dynamic programming.[17]
  • The image above says a lot about Dynamic Programming.[18]
  • Dynamic programming is basically, recursion plus using common sense.[18]
  • Using dynamic programming in the calculation of the nth member of the Fibonacci sequence improves its performance greatly.[19]
  • Dynamic programming makes it possible to count the number of solutions without visiting them all.[19]
  • Matrix chain multiplication is a well-known example that demonstrates utility of dynamic programming.[19]

소스

  1. ↑ Systolic processing for dynamic programming problems
  2. ↑ Dynamic Programming
  3. ↑ An Introduction to the Analysis of Algorithms
  4. ↑ Learn Dynamic Programming with Online Courses and Lessons
  5. ↑ Understanding Dynamic Programming in theory and practice
  6. ↑ Decoding As Dynamic Programming For Recurrent Autoregressive Models
  7. ↑ 7.0 7.1 7.2 7.3 All You Need to Know About Dynamic Programming
  8. ↑ Encyclopedia of Mathematics
  9. ↑ 9.0 9.1 A graphical introduction to dynamic programming
  10. ↑ Dynamic programming example
  11. ↑ What is Dynamic Programming: Introduction, Characteristics, Elements
  12. ↑ 12.0 12.1 Using Dynamic Programming for Problem Solving
  13. ↑ 13.0 13.1 Dynamic Programming
  14. ↑ 14.0 14.1 14.2 14.3 What Is Dynamic Programming With Python Examples
  15. ↑ 15.0 15.1 Dynamic Programming
  16. ↑ Dynamic Programming
  17. ↑ 17.0 17.1 17.2 17.3 Demystifying Dynamic Programming
  18. ↑ 18.0 18.1 Introduction to Dynamic Programming 1 Tutorials & Notes
  19. ↑ 19.0 19.1 19.2 Dynamic programming

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Spacy 패턴 목록

  • [{'LOWER': 'dynamic'}, {'LEMMA': 'programming'}]
  • [{'LOWER': 'dynamic'}, {'LEMMA': 'optimization'}]
  • [{'LEMMA': 'DP'}]
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