dynamic-programming

I need to find the largest square of 1's in a giant file full of 1's and 0's. I know i have to use dynamic programming. I am storing it in a 2D array. Any help with the algorithm to find the largest square would be great, thanks! example input: 1 0 1 0 1 0 1 0 1 1 1 1 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 answer: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 My code so far: int Square (Sq[int x][int y]) { if (Sq[x][y]) == 0) { return 0; } else { return 1+MIN( Sq(X-1,Y), Sq(X,Y-1), Sq(X-1,Y-1) ); } } (assuming values already entered into the array) int main() { int Sq[5][6]; //5,6 = bottom right conner int X =

What is the difference between memoization and dynamic programming? I think dynamic programming is a subset of memoization. Is it right? 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, iteratively and is applicable when the computations of the subproblems overlap. Dynamic programming is typically implemented using tabulation, but

I am working on this problem: The Subset Sum problem takes as input a set X = {x1, x2 ,…, xn} of n integers and another integer K . The problem is to check if there exists a subset X' of X whose elements sum to K and finds the subset if there's any. For example, if X = {5, 3, 11, 8, 2} and K = 16 then the answer is YES since the subset X' = {5, 11} has a sum of 16 . Implement an algorithm for Subset Sum whose run time is at least O(nK) . Notice complexity O(nK) . I think dynamic programming may help. I have found an exponential time algorithm, but it doesn't help. Can someone help me solve