I have a large matrix-M, and the rows have been sorted based on the value on some entry. Next I want to identify all rows that can be dominated, i.e., row #i is dominated by #j if j<i and M(j,:)<=M(i,:).
If rows #i is dominated, we can remove row i. I notice that remove row #i takes a lot of time for a large matrix so I set a index() and each time if it is dominated then index(i)=1. At last, M(index)=. (remove those dominated rows at last)
I run my code several times, and find out there is a bottleneck-N loops. Below I show some code:
for i=3:N j=2; %j from i-1 to may be faster! while j<=i-1 if all(M(j,1:N)<=M(i,1:N)) idx(i)=1; break; else j=j+1; end end end
I am thinking if someone can help me to optimize the code? Can we do better here? Thanks.
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