Difference between Divide and Conquer Algo and Dynamic Programming

Divide and Conquer Divide and Conquer works by dividing the problem into sub-problems, conquer each sub-problem recursively and combine these solutions. Dynamic Programming Dynamic Programming is a technique for solving problems with overlapping subproblems. Each sub-problem is solved only once and the result of each sub-problem is stored in a table ( generally implemented as … Read more

How to determine the longest increasing subsequence using dynamic programming?

OK, I will describe first the simplest solution which is O(N^2), where N is the size of the collection. There also exists a O(N log N) solution, which I will describe also. Look here for it at the section Efficient algorithms. I will assume the indices of the array are from 0 to N – … Read more

What is the difference between bottom-up and top-down?

rev4: A very eloquent comment by user Sammaron has noted that, perhaps, this answer previously confused top-down and bottom-up. While originally this answer (rev3) and other answers said that “bottom-up is memoization” (“assume the subproblems”), it may be the inverse (that is, “top-down” may be “assume the subproblems” and “bottom-up” may be “compose the subproblems”). … Read more

What is the difference between memoization and dynamic programming?

Relevant article on Programming.Guide: Dynamic programming vs memoization vs tabulation What is difference between memoization and dynamic programming? Memoization is a term describing an optimization technique where you cache previously computed results, and return the cached result when the same computation is needed again. Dynamic programming is a technique for solving problems of recursive nature, … Read more

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