#include
#include
#include
#include
using namespace std;
// It is not advisable to list all elements in this hash table.
#define HASH_SIZE 51439
class HashTable
{
public:
vector< map > table;
HashTable()
{
table = vector< map >(HASH_SIZE);
}
int hashF(long long key)
{
if( ke
you can write a python program to do that easily.
program starts here :
c=str.split(raw_input())
d=[]
for x in c:
d[x]=0
print list(d)
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correctness is by induction on number of
cycles.
thx
aj
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well the set (X + Y) will have O(n^2) elements, where X and Y have n
elements.
As an example
X = {1, 2}
Y = {3, 5}
X + Y = {1 + 3, 1 + 5, 2 + 3, 2 + 5} = {4, 5, 6, 7}
Now the problem is to find the median of X + Y in subquadratic time.
thx
aj
How about finding the median of (X + Y) in subquadratic time.
X + Y = {z | z = xi + yj for some i and j}.
I could only reduce the space complexity from O(n^2) to O(n) but time
complexity still
remains O(n^2).
thx
Aj
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that's right, it has worst case quadratic time complexity.
W Karas wrote:
> aj wrote:
> > linear worst case time.
>
> The best I can do is:
>
> bool is_palin(const char x[], unsigned len)
> {
> if (len < 2)
> return(true);
> for (u
linear worst case time.
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hi daizi,
I was expecting a solution that does not use suffix trees.
Using suffix trees
the problem can be solved easily, but I was just wondering if it is
mandatory to use
complex data structures like suffix trees to solve this problem.
thx
aj
Given a binary string x of length n, find the longest prefix of x in
linear time which is a palindrome.
thx
aj
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gth of
the subsequence) then your solution is excellent with O(n) time and
O(1) space complexity.
thx
Aj
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hey syed,
where are you right now? me at EPFL, switzerland. By the
way your solution is same as mine (dynamic programming one).
Aj
B.Tech (CSE), IIT Kanpur '03
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with at least L elements.
I hope I didnt misunderstood what you wanted to say
Aj
ps: in your code there is no guarntee that the the subsequence has at
least L elements.
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pe it helps
Aj
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the matrix
1 1 1
1 1 1
1 1 1
has rank 1, but is still rearrangable, so it seems linear dependence
has not much to do with the problem.
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SPX2 wrote:
> what complexity aj ?
O(ne) where e is the n is the number of rows and e is the number of 1's
in the matrix.
worst case O(n^3).
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entries 1 (r < k), and in that case even permuting columns will not
help as these k rows can cover at most r diagonals, i.e., A is not
rearrangable.
hope it helps
Aj
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scheduling, or this
small modification moves the problem from the class P to the class of
NP-complete.
thanks in advance
Aj
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