4-sum algorithm optimization

Question

I'm trying to map this problem into a 4-sum problem, and I find the time complexity is always \$O(n^3)\$. Is there a way to optimize time complexity, with constant additional space complexity \$O(1)\$?

Any other advice about improvement for time complexity, code bugs or code style advice is appreciated.

Problem

Given an array A of unique integers, find the index of values that satisfy A + B =C + D, where A,B,C & D are integers values in the array. Find all combinations of quadruples.

def four_sum (numbers, target, start, end, exclude_index_set):
    i = start
    j = end
    result = []
    while i < j:
        if i in exclude_index_set:
            i += 1
        elif j in exclude_index_set:
            j -= 1
        elif numbers[i] + numbers[j] == target:
            result.append((numbers[i], numbers[j]))
            i += 1
            j -= 1
        elif numbers[i] + numbers[j] > target:
            j -= 1
        else:
            i += 1
    return result

if __name__ == "__main__":
    numbers = [1,2,3,4]
    result = []
    for i,v in enumerate(numbers):
        for j in range(i+1, len(numbers)):
            r = four_sum(numbers, v+numbers[j], i+1, len(numbers)-1, set([i,j]))
            if len(r) > 0:
                r.append(([numbers[i],numbers[j]]))
                result.append(r)
    print result