'Longest simple path problem' presentation slideshows

Dynamic Programming I

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NP-Complete Problems (Fun part)

NP-Complete Problems (Fun part). Polynomial time vs exponential time Polynomial O(n k ), where n is the input size (e.g., number of nodes in a graph, the length of strings , etc) of our problem and k is a constant (e.g., k=1, 2, 3, etc). Exponential time: 2 n or n n .

563 views • 51 slides

Lecture 9 Dynamic programming

Lecture 9 Dynamic programming. What is Dynamic Programming How to write Dynamic Programming paradigm When to apply Dynamic Programming. Roadmap. What is Dynamic Programming How to write DP paradigm Knapsack problem Longest common subsequence Matrix chain multiplication

395 views • 39 slides