Sequential Methods
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Home > Art, Film & Photography > Sequential Methods: Dynamic Programming, Sequential Experiments, Knapsack Problem, Subset Sum Problem, Earley Parser
Sequential Methods: Dynamic Programming, Sequential Experiments, Knapsack Problem, Subset Sum Problem, Earley Parser

Sequential Methods: Dynamic Programming, Sequential Experiments, Knapsack Problem, Subset Sum Problem, Earley Parser


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About the Book

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 62. Chapters: Dynamic programming, Sequential experiments, Knapsack problem, Subset sum problem, Earley parser, Longest common subsequence problem, Forward-backward algorithm, Secretary problem, Viterbi algorithm, Bellman equation, Floyd-Warshall algorithm, Smith-Waterman algorithm, Levenshtein distance, Markov decision process, Gittins index, Multi-armed bandit, Matrix chain multiplication, Longest increasing subsequence, Approximate string matching, Word wrap, Response surface methodology, Backward induction, Partially observable Markov decision process, Needleman-Wunsch algorithm, Curse of dimensionality, Sequential probability ratio test, Longest common substring problem, Hamilton-Jacobi-Bellman equation, Hirschberg's algorithm, Sequential analysis, CUSUM, Optimal stopping, Optimal substructure, Maximum subarray problem, Pocock boundary, Haybittle-Peto boundary, Viscosity solution, Neyer d-optimal test, Bitonic tour, Shortest common supersequence, Hunt-McIlroy algorithm, Overlapping subproblem, Sequential estimation. Excerpt: In mathematics and computer science, dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems. It is applicable to problems exhibiting the properties of overlapping subproblems which are only slightly smaller and optimal substructure (described below). When applicable, the method takes far less time than naive methods. The key idea behind dynamic programming is quite simple. In general, to solve a given problem, we need to solve different parts of the problem (subproblems), then combine the solutions of the subproblems to reach an overall solution. Often, many of these subproblems are really the same. The dynamic programming approach seeks to solve each subproblem only once, thus reducing the number of computations. This is especially useful when the num...


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Product Details
  • ISBN-13: 9781156670385
  • Publisher: Books LLC, Wiki Series
  • Publisher Imprint: Books LLC, Wiki Series
  • Height: 246 mm
  • No of Pages: 64
  • Spine Width: 3 mm
  • Weight: 132 gr
  • ISBN-10: 1156670381
  • Publisher Date: 26 Jul 2011
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Dynamic Programming, Sequential Experiments, Knapsack Problem, Subset Sum Problem, Earley Parser
  • Width: 189 mm


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